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TransformerTags — scikit-learn 1.7.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version TransformerTags # class sklearn.utils. TransformerTag...scikit-learn.org/stable/modules/generated/sklearn.utils.TransformerTags.html -
IsolationForest — scikit-learn 1.7.1 documentation
Gallery examples: IsolationForest example Comparing anomaly detection algorithms for outlier detection on toy datasets Evaluation of outlier detection estimatorsscikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html -
LinearSVR — scikit-learn 1.7.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version LinearSVR # class sklearn.svm. LinearSVR ( * , epsilo...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVR.html -
sklearn — scikit-learn 1.7.1 documentation
Configure global settings and get information about the working environment.scikit-learn.org/stable/api/sklearn.html -
GaussianNB — scikit-learn 1.7.1 documentation
Gallery examples: Probability calibration of classifiers Probability Calibration curves Comparison of Calibration of Classifiers Classifier comparison Plotting Learning Curves and Checking Models’ ...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
BernoulliNB — scikit-learn 1.7.1 documentation
Gallery examples: Hashing feature transformation using Totally Random Treesscikit-learn.org/stable/modules/generated/sklearn.naive_bayes.BernoulliNB.html -
SVR — scikit-learn 1.7.1 documentation
Gallery examples: Prediction Latency Comparison of kernel ridge regression and SVR Support Vector Regression (SVR) using linear and non-linear kernelsscikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html -
MultiOutputClassifier — scikit-learn 1.7.1 docu...
Skip to main content Back to top Ctrl + K GitHub Choose version MultiOutputClassifier # class sklearn.multioutput. Mu...scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputClassifier.html -
ConstantKernel — scikit-learn 1.7.1 documentation
Gallery examples: Iso-probability lines for Gaussian Processes classification (GPC) Illustration of prior and posterior Gaussian process for different kernelsscikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ConstantKernel.html -
CompoundKernel — scikit-learn 1.7.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version CompoundKernel # class sklearn.gaussian_process.kerne...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.CompoundKernel.html