How to change the RandomForestClassifier in Python scikit-learn
0
How can I change the RandomForestClassifier in scikit-learn so that instead of holding in each terminal node the classes distribution. I'll go through all the records (in each terminal node) and run a formula such as linear regression?
# Import the random forest package
from sklearn.ensemble import RandomForestClassifier
# Create the random forest object which will include all the parameters
# for the fit
forest = RandomForestClassifier(n_estimators = 1)
#Take the same decision trees and run it on the test data
output = forest.predict(test_data)
python scikit-learn random-forest
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
add a comment |
0
How can I change the RandomForestClassifier in scikit-learn so that instead of holding in each terminal node the classes distribution. I'll go through all the records (in each terminal node) and run a formula such as linear regression?
# Import the random forest package
from sklearn.ensemble import RandomForestClassifier
# Create the random forest object which will include all the parameters
# for the fit
forest = RandomForestClassifier(n_estimators = 1)
#Take the same decision trees and run it on the test data
output = forest.predict(test_data)
python scikit-learn random-forest
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
1
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39
add a comment |
0
0
0
1
How can I change the RandomForestClassifier in scikit-learn so that instead of holding in each terminal node the classes distribution. I'll go through all the records (in each terminal node) and run a formula such as linear regression?
# Import the random forest package
from sklearn.ensemble import RandomForestClassifier
# Create the random forest object which will include all the parameters
# for the fit
forest = RandomForestClassifier(n_estimators = 1)
#Take the same decision trees and run it on the test data
output = forest.predict(test_data)
python scikit-learn random-forest
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
How can I change the RandomForestClassifier in scikit-learn so that instead of holding in each terminal node the classes distribution. I'll go through all the records (in each terminal node) and run a formula such as linear regression?
# Import the random forest package
from sklearn.ensemble import RandomForestClassifier
# Create the random forest object which will include all the parameters
# for the fit
forest = RandomForestClassifier(n_estimators = 1)
#Take the same decision trees and run it on the test data
output = forest.predict(test_data)
python scikit-learn random-forest
python scikit-learn random-forest
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
asked Nov 21 '18 at 16:57
AviAvi
1,0311634
1,0311634
1
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39
add a comment |
1
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39
1
1
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39
add a comment |
0
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1
Please specify more about what you want, preferably with an example
– Vivek Kumar
Nov 22 '18 at 7:16
I would like to add to each cluster a model. It means, that if RandomForest has 3 terminal nodes: A, B and C. I'll go to all records (in training) that are A and run a linear regression for them. Same for B and C.
– Avi
Nov 22 '18 at 7:39