Привет, меня зовут Артем. Сегодня я проверю твой проект.
Дальнейшее общение будет происходить на "ты" если это не вызывает никаких проблем.
Желательно реагировать на каждый мой комментарий ('исправил', 'не понятно как исправить ошибку', ...)
Пожалуйста, не удаляй комментарии ревьюера, так как они повышают качество повторного ревью.
Комментарии будут в зеленой, синей или красной рамках:
Будет очень хорошо, если ты будешь помечать свои действия следующим образом:
Полезные ссылки:¶
- Полезная лекция про временные ряды: https://www.youtube.com/watch?v=u433nrxdf5k .
Общее впечатление¶
- Большое спасибо за проделанную работу. Видно, что приложено много усилий.
- Отлично, что ноутбук хорошо структурирован. Приятно проверять такие работы.
- Над этим проектом нужно будет еще немного поработать. Однако, изменения не должны занять много времени.
- В работе я оставил несколько советов. Буду рад, если ты учтешь их.
- С радостью отвечу на твои вопросы, если они есть. Лучше всего их собрать в следующей ячейке. Жду новую версию проекта.
Общее впечатление (ревью 2)¶
- После исправлений проект улучшился и теперь он может быть зачтен.
- Для удобства все новые комментарии обозначены фразой "ревью 2".
- Удачи в дальнейшем обучении и следующих работах!
Прогнозирование заказов такси¶
Компания «Чётенькое такси» собрала исторические данные о заказах такси в аэропортах. Чтобы привлекать больше водителей в период пиковой нагрузки, нужно спрогнозировать количество заказов такси на следующий час. Постройте модель для такого предсказания.
Значение метрики RMSE на тестовой выборке должно быть не больше 48.
Вам нужно:
- Загрузить данные и выполнить их ресемплирование по одному часу.
- Проанализировать данные.
- Обучить разные модели с различными гиперпараметрами. Сделать тестовую выборку размером 10% от исходных данных.
- Проверить данные на тестовой выборке и сделать выводы.
Данные лежат в файле taxi.csv. Количество заказов находится в столбце num_orders (от англ. number of orders, «число заказов»).
Подготовка¶
# %pip install catboost
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import sklearn
from sklearn.linear_model import LinearRegression
from sklearn.ensemble import RandomForestRegressor
from sklearn.tree import DecisionTreeRegressor
from sklearn.model_selection import GridSearchCV, TimeSeriesSplit
from catboost import CatBoostRegressor
from sklearn.dummy import DummyRegressor
from statsmodels.tsa.seasonal import seasonal_decompose
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_absolute_error
import lightgbm as lgb
import warnings
try:
df = pd.read_csv('c:/users/norfolk/documents/python/datasets/taxi.csv',index_col=[0], parse_dates=[0])
except:
df = pd.read_csv('/datasets/taxi.csv',index_col=[0], parse_dates=[0])
size_a = len(df)
df.head()
| num_orders | |
|---|---|
| datetime | |
| 2018-03-01 00:00:00 | 9 |
| 2018-03-01 00:10:00 | 14 |
| 2018-03-01 00:20:00 | 28 |
| 2018-03-01 00:30:00 | 20 |
| 2018-03-01 00:40:00 | 32 |
df.info()
<class 'pandas.core.frame.DataFrame'> DatetimeIndex: 26496 entries, 2018-03-01 00:00:00 to 2018-08-31 23:50:00 Data columns (total 1 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 num_orders 26496 non-null int64 dtypes: int64(1) memory usage: 414.0 KB
df.isna().sum()
num_orders 0 dtype: int64
df.sort_index(inplace=True)
df = df.resample('1H').sum()
df.plot(grid = True)
plt.title('Рассемплированые данные по 1 часу')
plt.xlabel('Date')
plt.ylabel('Orders')
Text(0, 0.5, 'Orders')
Вывод: Данные загрузили. Каких либо проблем не выявленно: пропусков нет, дата в нужном нам формате. Произвели ресемплирование по 1 часу.
Анализ¶
df.rolling(15).mean().plot(grid = True)
plt.title('Сглаженный кадром набор данных')
plt.xlabel('Date')
plt.ylabel('Orders')
Text(0, 0.5, 'Orders')
decomposed = seasonal_decompose(df)
decomposed.seasonal['2018-04-01'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Сезонность за 1 день')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.seasonal['2018-04-01':'2018-04-03'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Сезонность за 3 дня')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.seasonal['2018-05-01':'2018-05-31'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Сезонность за месяц')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.seasonal.plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Сезонность за все время')
plt.xlabel('Date')
plt.ylabel('Orders')
Text(0, 0.5, 'Orders')
decomposed.trend['2018-04-01'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Тренд за 1 день')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.trend['2018-04-01':'2018-04-03'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Тренд за 3 дня')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.trend['2018-05-01':'2018-05-31'].plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Тренд за месяц')
plt.xlabel('Date')
plt.ylabel('Orders')
plt.show()
decomposed.trend.plot(xlabel ='Date', ylabel='orders',grid = True)
plt.title('Тренд за все время')
plt.xlabel('Date')
plt.ylabel('Orders')
Text(0, 0.5, 'Orders')
df_line = df-df.shift()
df_line['mean'] = df_line['num_orders'].rolling(15).mean()
df_line['std'] = df_line['num_orders'].rolling(15).std()
df_line.plot(title='Средние показатели', xlabel ='Date', ylabel='orders',grid = True)
<AxesSubplot:title={'center':'Средние показатели'}, xlabel='Date', ylabel='orders'>
Выводы:
1) Присутствует сезон по всему временному ряду. Минимальное число заказов в 6:00, а максимум в районе 0 часов.
2) Присутствует тренд в течении дня. Количество заказов плавно растет.
3) Исходя из графика средних показателей, можно сделать вывод что наш временной ряд стационарен. Т.к. среднее и стандартное отклонение практически не меняются.
Обучение¶
Создание признаков¶
def make_features(data, max_lag, rolling_mean_size):
df['month'] = df.index.month
df['day'] = df.index.day
df['dayofweek'] = df.index.dayofweek
df['hour'] = df.index.hour
for lag in range(1, max_lag):
df['lag_{}'.format(lag)] = df['num_orders'].shift(lag)
df['rolling_mean'] = df['num_orders'].shift().rolling(1).mean()
df.dropna(inplace=True)
return data
make_features(df, 26, 15)
print(df.columns)
Index(['num_orders', 'month', 'day', 'dayofweek', 'hour', 'lag_1', 'lag_2',
'lag_3', 'lag_4', 'lag_5', 'lag_6', 'lag_7', 'lag_8', 'lag_9', 'lag_10',
'lag_11', 'lag_12', 'lag_13', 'lag_14', 'lag_15', 'lag_16', 'lag_17',
'lag_18', 'lag_19', 'lag_20', 'lag_21', 'lag_22', 'lag_23', 'lag_24',
'lag_25', 'rolling_mean'],
dtype='object')
Совет: Желательно было написать функцию таким образом, чтобы она возвращала новый датафрейм, а не изменяла глобальную переменную.
- Это хорошая практика (не изменять глобальные переменные внутри функции), которая улучшает читаемость кода.
- В какой-то момент может появиться необходимость подбирать некоторые параметры используемый внутри функции. В этот момент копирование датасета станет обязательным.
Комментарий студента: Согласен полностью. Поэтому функция и вызов в отдельной ячейке, при отладке проблемы удалось избежать.
Подговка данных для моделей¶
train, test = train_test_split(df, shuffle=False, test_size=0.1)
features_train = train.drop(['num_orders'], axis=1)
target_train = train['num_orders']
features_test = test.drop(['num_orders'], axis=1)
target_test = test['num_orders']
Линейная ригрессия¶
model = LinearRegression()
model.fit(features_train, target_train)
pred_train = model.predict(features_train)
pred_test = model.predict(features_test)
print("RMSE обучающей выборки:", mean_squared_error(target_train, pred_train)**0.5)
RMSE обучающей выборки: 25.681828044006707
Вывод: Линейная регрессия дала нам следующий результат на обучающей выборке RMSE : 27.75
Дерево решений¶
warnings.filterwarnings('ignore')
splits = TimeSeriesSplit(n_splits=3)
model = DecisionTreeRegressor(random_state=12345)
parameters = {'max_depth':range(1,11,1)}
gsearch = GridSearchCV(estimator=model, cv=splits, param_grid=parameters, scoring='neg_mean_squared_error', verbose=3)
gsearch.fit(features_train, target_train)
print('Параметры:', gsearch.best_params_)
print('RMSE ', round(abs(gsearch.best_score_)**0.5))
Fitting 3 folds for each of 10 candidates, totalling 30 fits
[CV 1/3] END ....................max_depth=1;, score=-958.298 total time= 0.0s
[CV 2/3] END ...................max_depth=1;, score=-1107.106 total time= 0.0s
[CV 3/3] END ...................max_depth=1;, score=-2109.333 total time= 0.0s
[CV 1/3] END ....................max_depth=2;, score=-902.736 total time= 0.0s
[CV 2/3] END ....................max_depth=2;, score=-874.686 total time= 0.0s
[CV 3/3] END ...................max_depth=2;, score=-1690.644 total time= 0.0s
[CV 1/3] END ....................max_depth=3;, score=-912.786 total time= 0.0s
[CV 2/3] END ....................max_depth=3;, score=-873.990 total time= 0.0s
[CV 3/3] END ...................max_depth=3;, score=-1538.304 total time= 0.0s
[CV 1/3] END ....................max_depth=4;, score=-931.314 total time= 0.0s
[CV 2/3] END ....................max_depth=4;, score=-844.748 total time= 0.0s
[CV 3/3] END ...................max_depth=4;, score=-1402.764 total time= 0.0s
[CV 1/3] END ....................max_depth=5;, score=-930.048 total time= 0.0s
[CV 2/3] END ....................max_depth=5;, score=-905.239 total time= 0.0s
[CV 3/3] END ...................max_depth=5;, score=-1316.680 total time= 0.0s
[CV 1/3] END ....................max_depth=6;, score=-884.609 total time= 0.0s
[CV 2/3] END ...................max_depth=6;, score=-1006.099 total time= 0.0s
[CV 3/3] END ...................max_depth=6;, score=-1217.446 total time= 0.0s
[CV 1/3] END ...................max_depth=7;, score=-1079.051 total time= 0.0s
[CV 2/3] END ...................max_depth=7;, score=-1036.443 total time= 0.0s
[CV 3/3] END ...................max_depth=7;, score=-1310.114 total time= 0.0s
[CV 1/3] END ...................max_depth=8;, score=-1154.741 total time= 0.0s
[CV 2/3] END ...................max_depth=8;, score=-1105.401 total time= 0.0s
[CV 3/3] END ...................max_depth=8;, score=-1363.429 total time= 0.0s
[CV 1/3] END ...................max_depth=9;, score=-1136.225 total time= 0.0s
[CV 2/3] END ...................max_depth=9;, score=-1127.332 total time= 0.0s
[CV 3/3] END ...................max_depth=9;, score=-1621.441 total time= 0.0s
[CV 1/3] END ..................max_depth=10;, score=-1137.603 total time= 0.0s
[CV 2/3] END ..................max_depth=10;, score=-1268.514 total time= 0.0s
[CV 3/3] END ..................max_depth=10;, score=-1671.436 total time= 0.0s
Параметры: {'max_depth': 6}
RMSE 32
Вывод: Древо решений дало нам следующий результат на обучающей выборке RMSE : 32 при максимальной глубине равной 6
Случайный лес регрессии¶
model = RandomForestRegressor(random_state=12345)
parameters = {'n_estimators':range(50,100,10), 'max_depth':range(1,11,2)}
gsearch = GridSearchCV(estimator=model,cv=splits, param_grid=parameters, scoring='neg_mean_squared_error',verbose=3)
gsearch.fit(features_train, target_train)
print('Параметры:', gsearch.best_params_)
print('RMSE ', round(abs(gsearch.best_score_)**0.5))
Fitting 3 folds for each of 25 candidates, totalling 75 fits
[CV 1/3] END ...max_depth=1, n_estimators=50;, score=-908.803 total time= 0.0s
[CV 2/3] END ..max_depth=1, n_estimators=50;, score=-1106.689 total time= 0.0s
[CV 3/3] END ..max_depth=1, n_estimators=50;, score=-2130.852 total time= 0.1s
[CV 1/3] END ...max_depth=1, n_estimators=60;, score=-911.945 total time= 0.0s
[CV 2/3] END ..max_depth=1, n_estimators=60;, score=-1109.006 total time= 0.0s
[CV 3/3] END ..max_depth=1, n_estimators=60;, score=-2126.960 total time= 0.1s
[CV 1/3] END ...max_depth=1, n_estimators=70;, score=-913.492 total time= 0.0s
[CV 2/3] END ..max_depth=1, n_estimators=70;, score=-1106.218 total time= 0.1s
[CV 3/3] END ..max_depth=1, n_estimators=70;, score=-2127.559 total time= 0.1s
[CV 1/3] END ...max_depth=1, n_estimators=80;, score=-912.209 total time= 0.0s
[CV 2/3] END ..max_depth=1, n_estimators=80;, score=-1105.466 total time= 0.1s
[CV 3/3] END ..max_depth=1, n_estimators=80;, score=-2130.176 total time= 0.1s
[CV 1/3] END ...max_depth=1, n_estimators=90;, score=-914.198 total time= 0.1s
[CV 2/3] END ..max_depth=1, n_estimators=90;, score=-1106.294 total time= 0.1s
[CV 3/3] END ..max_depth=1, n_estimators=90;, score=-2133.504 total time= 0.2s
[CV 1/3] END ...max_depth=3, n_estimators=50;, score=-753.586 total time= 0.1s
[CV 2/3] END ...max_depth=3, n_estimators=50;, score=-749.349 total time= 0.2s
[CV 3/3] END ..max_depth=3, n_estimators=50;, score=-1466.254 total time= 0.3s
[CV 1/3] END ...max_depth=3, n_estimators=60;, score=-752.536 total time= 0.1s
[CV 2/3] END ...max_depth=3, n_estimators=60;, score=-744.885 total time= 0.2s
[CV 3/3] END ..max_depth=3, n_estimators=60;, score=-1461.626 total time= 0.4s
[CV 1/3] END ...max_depth=3, n_estimators=70;, score=-755.549 total time= 0.1s
[CV 2/3] END ...max_depth=3, n_estimators=70;, score=-746.459 total time= 0.3s
[CV 3/3] END ..max_depth=3, n_estimators=70;, score=-1461.241 total time= 0.4s
[CV 1/3] END ...max_depth=3, n_estimators=80;, score=-756.927 total time= 0.2s
[CV 2/3] END ...max_depth=3, n_estimators=80;, score=-744.638 total time= 0.3s
[CV 3/3] END ..max_depth=3, n_estimators=80;, score=-1468.678 total time= 0.5s
[CV 1/3] END ...max_depth=3, n_estimators=90;, score=-755.207 total time= 0.2s
[CV 2/3] END ...max_depth=3, n_estimators=90;, score=-747.124 total time= 0.4s
[CV 3/3] END ..max_depth=3, n_estimators=90;, score=-1471.762 total time= 0.6s
[CV 1/3] END ...max_depth=5, n_estimators=50;, score=-666.541 total time= 0.1s
[CV 2/3] END ...max_depth=5, n_estimators=50;, score=-671.063 total time= 0.3s
[CV 3/3] END ..max_depth=5, n_estimators=50;, score=-1232.225 total time= 0.5s
[CV 1/3] END ...max_depth=5, n_estimators=60;, score=-660.335 total time= 0.2s
[CV 2/3] END ...max_depth=5, n_estimators=60;, score=-669.506 total time= 0.4s
[CV 3/3] END ..max_depth=5, n_estimators=60;, score=-1228.694 total time= 0.6s
[CV 1/3] END ...max_depth=5, n_estimators=70;, score=-660.506 total time= 0.2s
[CV 2/3] END ...max_depth=5, n_estimators=70;, score=-669.316 total time= 0.5s
[CV 3/3] END ..max_depth=5, n_estimators=70;, score=-1230.549 total time= 0.8s
[CV 1/3] END ...max_depth=5, n_estimators=80;, score=-665.731 total time= 0.3s
[CV 2/3] END ...max_depth=5, n_estimators=80;, score=-667.179 total time= 0.6s
[CV 3/3] END ..max_depth=5, n_estimators=80;, score=-1226.712 total time= 0.9s
[CV 1/3] END ...max_depth=5, n_estimators=90;, score=-661.751 total time= 0.3s
[CV 2/3] END ...max_depth=5, n_estimators=90;, score=-668.527 total time= 0.7s
[CV 3/3] END ..max_depth=5, n_estimators=90;, score=-1224.333 total time= 1.0s
[CV 1/3] END ...max_depth=7, n_estimators=50;, score=-620.508 total time= 0.2s
[CV 2/3] END ...max_depth=7, n_estimators=50;, score=-625.376 total time= 0.5s
[CV 3/3] END ..max_depth=7, n_estimators=50;, score=-1112.066 total time= 0.8s
[CV 1/3] END ...max_depth=7, n_estimators=60;, score=-615.918 total time= 0.3s
[CV 2/3] END ...max_depth=7, n_estimators=60;, score=-624.148 total time= 0.6s
[CV 3/3] END ..max_depth=7, n_estimators=60;, score=-1110.971 total time= 0.9s
[CV 1/3] END ...max_depth=7, n_estimators=70;, score=-616.814 total time= 0.3s
[CV 2/3] END ...max_depth=7, n_estimators=70;, score=-620.677 total time= 0.7s
[CV 3/3] END ..max_depth=7, n_estimators=70;, score=-1111.238 total time= 1.1s
[CV 1/3] END ...max_depth=7, n_estimators=80;, score=-622.238 total time= 0.4s
[CV 2/3] END ...max_depth=7, n_estimators=80;, score=-618.133 total time= 0.8s
[CV 3/3] END ..max_depth=7, n_estimators=80;, score=-1102.475 total time= 1.3s
[CV 1/3] END ...max_depth=7, n_estimators=90;, score=-620.556 total time= 0.5s
[CV 2/3] END ...max_depth=7, n_estimators=90;, score=-618.861 total time= 1.0s
[CV 3/3] END ..max_depth=7, n_estimators=90;, score=-1096.847 total time= 1.5s
[CV 1/3] END ...max_depth=9, n_estimators=50;, score=-611.116 total time= 0.3s
[CV 2/3] END ...max_depth=9, n_estimators=50;, score=-609.733 total time= 0.6s
[CV 3/3] END ..max_depth=9, n_estimators=50;, score=-1060.800 total time= 1.0s
[CV 1/3] END ...max_depth=9, n_estimators=60;, score=-607.576 total time= 0.4s
[CV 2/3] END ...max_depth=9, n_estimators=60;, score=-608.872 total time= 0.8s
[CV 3/3] END ..max_depth=9, n_estimators=60;, score=-1062.852 total time= 1.2s
[CV 1/3] END ...max_depth=9, n_estimators=70;, score=-607.167 total time= 0.4s
[CV 2/3] END ...max_depth=9, n_estimators=70;, score=-608.594 total time= 0.9s
[CV 3/3] END ..max_depth=9, n_estimators=70;, score=-1061.696 total time= 1.4s
[CV 1/3] END ...max_depth=9, n_estimators=80;, score=-608.683 total time= 0.5s
[CV 2/3] END ...max_depth=9, n_estimators=80;, score=-604.144 total time= 1.1s
[CV 3/3] END ..max_depth=9, n_estimators=80;, score=-1056.465 total time= 1.7s
[CV 1/3] END ...max_depth=9, n_estimators=90;, score=-607.542 total time= 0.6s
[CV 2/3] END ...max_depth=9, n_estimators=90;, score=-604.633 total time= 1.2s
[CV 3/3] END ..max_depth=9, n_estimators=90;, score=-1050.870 total time= 1.9s
Параметры: {'max_depth': 9, 'n_estimators': 90}
RMSE 27
Вывод: Случайный лес регрессии дал нам следующий результат на обучающей выборке RMSE : 27 при максимальной глубине равной 9 и количество деревьев 90.
СatBoost модель¶
cat = CatBoostRegressor()
parametrs = {'depth' : [9,21],
'learning_rate' : [0.2, 0.05,1],
'iterations' : [400]
}
model = GridSearchCV(cat, parametrs, scoring='neg_mean_squared_error',cv = splits)
model.fit(features_train, target_train)
best_params_ = model.best_params_
print('Лучшие параметры ', model.best_params_)
print('rmse ', abs(model.best_score_)**0.5)
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Лучшие параметры {'depth': 9, 'iterations': 400, 'learning_rate': 0.05}
rmse 27.397357857433583
Вывод: CatBoost модель с подбором параметров дает нам метрику RMSE =27.4 с параметрами: depth=9, iterations=400, learning_rate = 0.05}. Увелечение этих параметров ведет к серьезному увелечению времени обучения
LGBM модель¶
%%time
lgbr = lgb.LGBMRegressor(random_state =12345)
parametrs = { 'max_depth' :[6],
'learning_rate' : [0.01, 0.015, 0.025, 0.05, 0.1],
'num_leaves' : [31 , 62 , 42],
'feature_fraction' : [0,6, 0,7, 0,8, 0,9, 1],
'min_split_gain' : [0, 0.05, 0.1, 0.3, 0.5, 0.7, 0.9, 1]
}
model = GridSearchCV(lgbr, parametrs, scoring='neg_mean_squared_error',cv = splits)
model.fit(features_train, target_train,verbose=False)
print('Лучшие параметры ', model.best_params_)
print('rmse ', abs(model.best_score_)**0.5)
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1
Лучшие параметры {'feature_fraction': 1, 'learning_rate': 0.1, 'max_depth': 6, 'min_split_gain': 0.05, 'num_leaves': 31}
rmse 26.50058396859625
Wall time: 32.2 s
Вывод: LGBM модель дает нам метрику RMSE = 26.5
Лучшие параметры {'feature_fraction': 1, 'learning_rate': 0.1, 'max_depth': 6, 'min_split_gain': 0.05, 'num_leaves': 31}
Общий вывод: Исходя из обученных моделей для теста берем модель CatBoostRegressor со стандартными гиперпараметрами.
Ошибка: Сравнение моделей нужно провести только на кросс-валидации grid.best_score_ (с одним и тем же параметром "cv") или только на валидационной выборке.
Тестирование¶
lgbr = lgb.LGBMRegressor(random_state =12345)
parametrs = { 'max_depth' :[6],
'learning_rate' : [0.1],
'num_leaves' : [31],
'feature_fraction' : [1],
'min_split_gain' : [0.05]
}
model = GridSearchCV(lgbr, parametrs, scoring='neg_mean_squared_error',cv = splits)
model.fit(features_train, target_train,verbose=False)
predictions = model.predict(features_test)
print("RMSE тестовой выборки:", mean_squared_error(target_test, predictions)**0.5)
[LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1 [LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1 [LightGBM] [Warning] feature_fraction is set=1, colsample_bytree=1.0 will be ignored. Current value: feature_fraction=1 RMSE тестовой выборки: 39.95219937027742
plt.figure(figsize=(12, 3))
plt.plot(target_test.index,
target_test,label='Test')
plt.plot(target_test.index, predictions, label='Predications')
plt.legend(['Test', 'Predications'])
plt.title('Качество модели, RMSE:{:.4}'.format(rmse))
plt.ylabel('Orders')
plt.xlabel('Datetime')
Text(0.5, 0, 'Datetime')
Вывод Качество модели нас устраивает, т.к. по условию метрика не должна превышать 48. Наш результат RMSE ~ 40
Проверка модели на адекватность¶
Предсказание медианой¶
pred_median = np.ones(test['num_orders'].shape) * train['num_orders'].median()
print("rmse:", mean_squared_error(test['num_orders']**0.5, pred_median))
rmse: 4034.1085823567364
Предсказание предыдущим значением¶
pred_previous = test['num_orders'].shift()
pred_previous.iloc[0] = train['num_orders'].iloc[-1]
print("rmse:", mean_squared_error(test['num_orders']**0.5, pred_previous))
rmse: 19660.646703931743
Проверка на адекватность DummyRegressor¶
dummy_regr = DummyRegressor(strategy="median")
dummy_regr.fit(features_train, target_train)
pred_dum = dummy_regr.predict(features_test)
print("rmse:", mean_squared_error(target_test, pred_dum)**0.5)
rmse: 87.21093811714634
Вывод: Наша модель значительно лучше моделей предсказания основанных на медиане и предстоящем значении. Dummy модель дала метрику RMSE = 87.21
Общий вывод: Проаналировав предоставленные нам данные, мы выявили сезонность и тренды. Определившись что наш временной ряд стационарен, мы приступили к построению моделей. Лучшей моделью для нас оказалась LGBMRegressor. Метрика на тестовой выборке составила RMSE ~ 40. Что удовлетворяет нашему изначальному заданию.
Чек-лист проверки¶
- Jupyter Notebook открыт
- Весь код выполняется без ошибок
- Ячейки с кодом расположены в порядке исполнения
- Данные загружены и подготовлены
- Данные проанализированы
- Модель обучена, гиперпараметры подобраны
- Качество моделей проверено, выводы сделаны
- Значение RMSE на тестовой выборке не больше 48