scikit-learn:3.5. Validation curves:plotting scores to evaluate models

Reference: http://scikit-learn.org/stable/modules/learning_curve.html

Estimator ' s generalization error can be decomposedin terms of bias, variance and noise. thebiasOf an estimator is it average error for different training sets. theVarianceOf an estimator indicates how sensitive it was to varying training sets. Noise is a property of the data.

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scikit-learn:3.5. Validation curves:plotting scores to evaluate models