ValueError: gbrt has to be an instance of BaseGradientBoosting
up vote
0
down vote
favorite
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 at 13:17
MD SIBGATULLAH AHMAD
12
add a comment |
up vote
0
down vote
favorite
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 at 13:17
MD SIBGATULLAH AHMAD
12
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
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 at 13:17
MD 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 at 13:17
MD SIBGATULLAH AHMAD
12
asked Nov 19 at 13:17
MD SIBGATULLAH AHMAD
12
edited Nov 19 at 14:28
asked Nov 19 at 13:17
MD SIBGATULLAH AHMAD
12
asked Nov 19 at 13:17
MD SIBGATULLAH AHMAD
12
asked Nov 19 at 13:17
MD SIBGATULLAH AHMAD
12
12
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
up vote
0
down vote
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 at 14:06
Bar
1,2341831
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
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 at 14:06
Bar
1,2341831
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
add a comment |
up vote
0
down vote
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 at 14:06
Bar
1,2341831
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
add a comment |
up vote
0
down vote
up vote
0
down vote
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 at 14:06
Bar
1,2341831
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 at 14:06
Bar
1,2341831
answered Nov 19 at 14:06
Bar
1,2341831
answered Nov 19 at 14:06
Bar
1,2341831
answered Nov 19 at 14:06
Bar
1,2341831
1,2341831
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 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 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Thank you very much. Indeed, I have to use GradientBoostingRegressor instead XGBRegressor for plotting.
– MD SIBGATULLAH AHMAD
Nov 19 at 14:30
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
Feel free to accept this answer if you feel it addresses your question.
– Bar
Nov 22 at 0:41
add a comment |
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53375496%2fvalueerror-gbrt-has-to-be-an-instance-of-basegradientboosting%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
