# Statistical foundations of machine learning

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## Table of contents

## Recently updated pages

Permutation test -
23 Feb 2014

Randomization tests -
23 Feb 2014

The bootstrap principle -
23 Feb 2014

Bootstrap estimate of bias -
23 Feb 2014

Bootstrap sampling -
23 Feb 2014

Bootstrap -
23 Feb 2014

Estimation of arbitrary statistics -
23 Feb 2014

Nonparametric methods -
23 Feb 2014

Receiver Operating Characteristic curve -
23 Feb 2014

A posteriori assessment of a test -
02 Feb 2014

## Statistics : Total views

Statistical foundations of machine learning - 8,686 | Bias/variance decomposition of MSE - 1,561 |

Introduction - 3,480 | Plug-in principle to define an estimator - 1,558 |

Modelling from data - 3,119 | The random model of uncertainty - 1,547 |

The sum of i.i.d. random variables - 2,569 | Stacked regression - 1,513 |

USPS dataset - 2,370 | Outline - 1,468 |

Foundations of probability - 2,198 | Classification and Regression Trees - 1,451 |

Stastistical machine learning - 2,036 | Bias and variance - 1,450 |

Bias and variance of $\hat \mu$ - 1,920 | Bivariate normal distribution - 1,447 |

Bias of the estimator $\hat \sigma^2$ - 1,748 | Classical parametric estimation - 1,436 |

Axiomatic definition of probability - 1,655 | Normal distribution: the scalar case - 1,417 |

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