ValueError: gbrt has to be an instance of BaseGradientBoosting
So I am trying to make partial dependence plot using xgboost in spyder. But it is giving ValueError: gbrt has to be an instance of BaseGradientBoosting. I have predefine values of train_X, train_y, val_X, val_y.
Here is the code:
from xgboost import XGBRegressor
model=XGBRegressor(n_estimator=1000, learning_rate=0.05)
model.fit(train_X, train_y, early_stopping_rounds=5, eval_set=[(val_X, val_y)], verbose=False)
pred_xgb=model.predict(val_X)
print(mean_absolute_error(pred_xgb, val_y),'is the mae n')
from sklearn.ensemble.partial_dependence import plot_partial_dependence
from sklearn.ensemble.partial_dependence import partial_dependence
plot=plot_partial_dependence(model,train_X, features=[1,3], feature_names=['mssubclass','mszoning','salestype','salescondition'], grid_resolution=20)
Thank you.
python dependencies data-science data-analysis xgboost
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
add a comment |
So I am trying to make partial dependence plot using xgboost in spyder. But it is giving ValueError: gbrt has to be an instance of BaseGradientBoosting. I have predefine values of train_X, train_y, val_X, val_y.
Here is the code:
from xgboost import XGBRegressor
model=XGBRegressor(n_estimator=1000, learning_rate=0.05)
model.fit(train_X, train_y, early_stopping_rounds=5, eval_set=[(val_X, val_y)], verbose=False)
pred_xgb=model.predict(val_X)
print(mean_absolute_error(pred_xgb, val_y),'is the mae n')
from sklearn.ensemble.partial_dependence import plot_partial_dependence
from sklearn.ensemble.partial_dependence import partial_dependence
plot=plot_partial_dependence(model,train_X, features=[1,3], feature_names=['mssubclass','mszoning','salestype','salescondition'], grid_resolution=20)
Thank you.
python dependencies data-science data-analysis xgboost
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
add a comment |
So I am trying to make partial dependence plot using xgboost in spyder. But it is giving ValueError: gbrt has to be an instance of BaseGradientBoosting. I have predefine values of train_X, train_y, val_X, val_y.
Here is the code:
from xgboost import XGBRegressor
model=XGBRegressor(n_estimator=1000, learning_rate=0.05)
model.fit(train_X, train_y, early_stopping_rounds=5, eval_set=[(val_X, val_y)], verbose=False)
pred_xgb=model.predict(val_X)
print(mean_absolute_error(pred_xgb, val_y),'is the mae n')
from sklearn.ensemble.partial_dependence import plot_partial_dependence
from sklearn.ensemble.partial_dependence import partial_dependence
plot=plot_partial_dependence(model,train_X, features=[1,3], feature_names=['mssubclass','mszoning','salestype','salescondition'], grid_resolution=20)
Thank you.
python dependencies data-science data-analysis xgboost
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
So I am trying to make partial dependence plot using xgboost in spyder. But it is giving ValueError: gbrt has to be an instance of BaseGradientBoosting. I have predefine values of train_X, train_y, val_X, val_y.
Here is the code:
from xgboost import XGBRegressor
model=XGBRegressor(n_estimator=1000, learning_rate=0.05)
model.fit(train_X, train_y, early_stopping_rounds=5, eval_set=[(val_X, val_y)], verbose=False)
pred_xgb=model.predict(val_X)
print(mean_absolute_error(pred_xgb, val_y),'is the mae n')
from sklearn.ensemble.partial_dependence import plot_partial_dependence
from sklearn.ensemble.partial_dependence import partial_dependence
plot=plot_partial_dependence(model,train_X, features=[1,3], feature_names=['mssubclass','mszoning','salestype','salescondition'], grid_resolution=20)
Thank you.
python dependencies data-science data-analysis xgboost
python dependencies data-science data-analysis xgboost
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
edited Nov 19 '18 at 14:28
MD SIBGATULLAH AHMAD
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
asked Nov 19 '18 at 13:17
MD SIBGATULLAH AHMADMD SIBGATULLAH AHMAD
12
12
add a comment |
add a comment |
1 Answer
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This is caused by an incompatibility between sklearn and xgboost.
plot_partial_dependence expects a model that inherits from BaseGradientBoosting that is a sklearn-specific class that XGBoostRegressor does not inherit from AFAIK.
That means that if you want to use that you would need to convert between the XGBoost model and an sklearn GBRT model. It might be possible to do that through treelite.
answered Nov 19 '18 at 14:06
BarBar
1,2891931
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
add a comment |
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
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active
oldest
votes
active
oldest
votes
This is caused by an incompatibility between sklearn and xgboost.
plot_partial_dependence expects a model that inherits from BaseGradientBoosting that is a sklearn-specific class that XGBoostRegressor does not inherit from AFAIK.
That means that if you want to use that you would need to convert between the XGBoost model and an sklearn GBRT model. It might be possible to do that through treelite.
answered Nov 19 '18 at 14:06
BarBar
1,2891931
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
add a comment |
This is caused by an incompatibility between sklearn and xgboost.
plot_partial_dependence expects a model that inherits from BaseGradientBoosting that is a sklearn-specific class that XGBoostRegressor does not inherit from AFAIK.
That means that if you want to use that you would need to convert between the XGBoost model and an sklearn GBRT model. It might be possible to do that through treelite.
answered Nov 19 '18 at 14:06
BarBar
1,2891931
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
add a comment |
This is caused by an incompatibility between sklearn and xgboost.
plot_partial_dependence expects a model that inherits from BaseGradientBoosting that is a sklearn-specific class that XGBoostRegressor does not inherit from AFAIK.
That means that if you want to use that you would need to convert between the XGBoost model and an sklearn GBRT model. It might be possible to do that through treelite.
answered Nov 19 '18 at 14:06
BarBar
1,2891931
This is caused by an incompatibility between sklearn and xgboost.
plot_partial_dependence expects a model that inherits from BaseGradientBoosting that is a sklearn-specific class that XGBoostRegressor does not inherit from AFAIK.
That means that if you want to use that you would need to convert between the XGBoost model and an sklearn GBRT model. It might be possible to do that through treelite.
answered Nov 19 '18 at 14:06
BarBar
1,2891931
answered Nov 19 '18 at 14:06
BarBar
1,2891931
answered Nov 19 '18 at 14:06
BarBar
1,2891931
answered Nov 19 '18 at 14:06
BarBar
1,2891931
1,2891931
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
add a comment |
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 '18 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 '18 at 0:41
add a comment |
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