python-scikit-learnGrid search CV example
from sklearn import svm, datasets, model_selection
iris = datasets.load_iris()
parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
clf = model_selection.GridSearchCV(svm.SVC(), parameters)
clf.fit(iris.data, iris.target)
results = clf.cv_results_ctrl + cfrom sklearn importimport module from scikit-learn | load_irisloads Iris dataset |
parametersparameters dictionary to run grid search accross | .GridSearchCV(creates GridSearchCV model |
svm.SVC()use SVC model as an estimator | .fit(train transformation model |
.cv_results_dictionary with results after model training and parameters search | |
Usage example
from sklearn import svm, datasets, model_selection
iris = datasets.load_iris()
parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
clf = model_selection.GridSearchCV(svm.SVC(), parameters)
clf.fit(iris.data, iris.target)
print(clf.cv_results_['params'])output
[{'C': 1, 'kernel': 'linear'}, {'C': 1, 'kernel': 'rbf'}, {'C': 10, 'kernel': 'linear'}, {'C': 10, 'kernel': 'rbf'}]
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