Hi,
I am using the following code for doing the Random Forest regression:
Random Forest Regressor
from sklearn.ensemble import RandomForestRegressor
rf = RandomForestRegressor(n_estimators = 10, random_state=42)
rf.fit(PDemand_prepared, PDemand_labels)
Model Fitting
PDemand_predictions = rf.predict(PDemand_prepared)
Getting error message -->
IndexError Traceback (most recent call last)
in
----> 1 PDemand_predictions = rf.predict(PDemand_prepared)
/usr/local/anaconda/lib/python3.6/site-packages/sklearn/ensemble/_forest.py in predict(self, X)
764 check_is_fitted(self)
765 # Check data
–> 766 X = self._validate_X_predict(X)
767
768 # Assign chunk of trees to jobs
/usr/local/anaconda/lib/python3.6/site-packages/sklearn/ensemble/_forest.py in validate_X_predict(self, X)
410 check_is_fitted(self)
411
–> 412 return self.estimators[0]._validate_X_predict(X, check_input=True)
413
414 @property
IndexError: list index out of range
Getting the same error “IndexError: list index out of range” while calculating RMSE of RF model
Calculate RMSE in Random Forest model
import numpy as np
from sklearn import metrics
PDemand_predictions = rf.predict(PDemand_prepared)
print(‘Root Mean Squared Error:’, np.sqrt(metrics.mean_squared_error(PDemand_labels, PDemand_predictions)))
IndexError Traceback (most recent call last)
in
3 from sklearn import metrics
4
----> 5 PDemand_predictions = rf.predict(PDemand_prepared)
6
7 print(‘Root Mean Squared Error:’, np.sqrt(metrics.mean_squared_error(PDemand_labels, PDemand_predictions)))
/usr/local/anaconda/lib/python3.6/site-packages/sklearn/ensemble/_forest.py in predict(self, X)
764 check_is_fitted(self)
765 # Check data
–> 766 X = self._validate_X_predict(X)
767
768 # Assign chunk of trees to jobs
/usr/local/anaconda/lib/python3.6/site-packages/sklearn/ensemble/_forest.py in validate_X_predict(self, X)
410 check_is_fitted(self)
411
–> 412 return self.estimators[0]._validate_X_predict(X, check_input=True)
413
414 @property
IndexError: list index out of range
Please advise how to fix this?
Thanks