gridsearchcv

问题 I've been attempting to fit a Grid Search K Nearest neighbors Classifier, but am receiving the following Error message TypeError : '<' not supported between instances of 'str' and 'int' X_train compact sa area roofM3 h o glaz glazing_area_distribution 0 0.66 759.5 318.5 220.50 3.5 2 0.40 3 1 0.76 661.5 416.5 122.50 7.0 3 0.10 1 2 0.66 759.5 318.5 220.50 3.5 3 0.10 1 3 0.74 686.0 245.0 220.50 3.5 5 0.10 4 4 0.64 784.0 343.0 220.50 3.5 2 0.40 4 ... ... ... ... ... ... ... ... ... 609 0.98 514.5

问题 I'm trying and failing to pass parameters to a custom estimator in scikit learn. I'd like the parameter lr to change during the gridsearch. Problem is that the lr parameter is not changing... The code sample is copied and updated from here (the original code did neither work for me) Any full working example of GridSearchCV with custom estimator, with changing parameters would be appreciated. I'm in ubuntu 18.10 using scikit-learn 0.20.2 from sklearn.model_selection import GridSearchCV from

问题 I'm trying and failing to pass parameters to a custom estimator in scikit learn. I'd like the parameter lr to change during the gridsearch. Problem is that the lr parameter is not changing... The code sample is copied and updated from here (the original code did neither work for me) Any full working example of GridSearchCV with custom estimator, with changing parameters would be appreciated. I'm in ubuntu 18.10 using scikit-learn 0.20.2 from sklearn.model_selection import GridSearchCV from

问题 I would like to use the AdaBoostClassifier with LinearSVC as base estimator. I want to do a gridsearch on some of the parameters in LinearSVC. Also I have to scale my features. p_grid = {'base_estimator__C': np.logspace(-5, 3, 10)} n_splits = 5 inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=5) SVC_Kernel=LinearSVC(multi_class ='crammer_singer',tol=10e-3,max_iter=10000,class_weight='balanced') ABC = AdaBoostClassifier(base_estimator=SVC_Kernel,n_estimators=600

问题 I would like to use the AdaBoostClassifier with LinearSVC as base estimator. I want to do a gridsearch on some of the parameters in LinearSVC. Also I have to scale my features. p_grid = {'base_estimator__C': np.logspace(-5, 3, 10)} n_splits = 5 inner_cv = StratifiedKFold(n_splits=n_splits, shuffle=True, random_state=5) SVC_Kernel=LinearSVC(multi_class ='crammer_singer',tol=10e-3,max_iter=10000,class_weight='balanced') ABC = AdaBoostClassifier(base_estimator=SVC_Kernel,n_estimators=600

问题 I want to subclass sklearn.svm.LinearSVC and use it as an estimator for sklearn.model_selection.GridSearchCV . I had some issues with subclassing earlier and I thought I fixed it based on my previous post and the selected answer. However, now my objective is to create an sklearn.kernel_approximation.RBFSampler object as an attribute of my new class. Now this is an example and I have a broader question here which is: Question: With the final expectation of using my new estimator class with

来源： https://stackoverflow.com/questions/59495505/attributeerror-str-object-has-no-attribute-parameters-due-to-new-version-of

来源： https://stackoverflow.com/questions/64430351/subclassing-sklearn-linearsvc-for-use-as-estimator-with-sklearn-gridsearchcv

来源： https://stackoverflow.com/questions/63533647/gridsearchcv-with-scoring-function-and-refit-parameter

来源： https://stackoverflow.com/questions/63533647/gridsearchcv-with-scoring-function-and-refit-parameter