# 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 - 2,778 | The machine learning procedure - 393 |

Introduction - 1,310 | Stacked regression - 329 |

Modelling from data - 1,087 | Maximum likelihood computation - 326 |

Foundations of probability - 628 | Introduction - 311 |

Stastistical machine learning - 601 | Curse of dimensionality - 307 |

Axiomatic definition of probability - 465 | Nonlinear approaches - 294 |

Feature selection - 458 | Notations - 292 |

Classical parametric estimation - 441 | Statistical supervised learning - 287 |

The random model of uncertainty - 436 | Bias and variance of $\hat \mu$ - 286 |

Outline - 407 | Bias of the estimator $\hat \sigma^2$ - 285 |

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