Issue
I was checking sklearn documentation webpage about GridSearchCV
.
One of attributes of GridSearchCV
object is best_estimator_
.
So here is my question. How to pass more than one estimator to GSCV object?
Using a dictionary like:
{'SVC()':{'C':10, 'gamma':0.01}, ' DecTreeClass()':{....}}
?
Solution
GridSearchCV works on parameters. It will train multiple estimators (but same class (one of SVC, or DecisionTreeClassifier, or other classifiers) with different parameter combinations from specified in param_grid
. best_estimator_
is the estimator which performs best on the data.
So essentially best_estimator_
is the same class object initialized with best found params.
So in the basic setup you cannot use multiple estimators in the grid-search.
But as a workaround, you can have multiple estimators when using a pipeline in which the estimator is a "parameter"
which the GridSearchCV can set.
Something like this:
from sklearn.pipeline import Pipeline
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import load_iris
iris_data = load_iris()
X, y = iris_data.data, iris_data.target
# Just initialize the pipeline with any estimator you like
pipe = Pipeline(steps=[('estimator', SVC())])
# Add a dict of estimator and estimator related parameters in this list
params_grid = [{
'estimator':[SVC()],
'estimator__C': [1, 10, 100, 1000],
'estimator__gamma': [0.001, 0.0001],
},
{
'estimator': [DecisionTreeClassifier()],
'estimator__max_depth': [1,2,3,4,5],
'estimator__max_features': [None, "auto", "sqrt", "log2"],
},
# {'estimator':[Any_other_estimator_you_want],
# 'estimator__valid_param_of_your_estimator':[valid_values]
]
grid = GridSearchCV(pipe, params_grid)
You can add as many dicts inside the list of params_grid
as you like, but make sure that each dict have compatible parameters related to the 'estimator'
.
Answered By - Vivek Kumar
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