# 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 - 10,479 | Bias of the estimator $\hat \sigma^2$ - 2,306 |

Introduction - 4,089 | Plug-in principle to define an estimator - 2,206 |

Modelling from data - 3,796 | Bivariate normal distribution - 2,202 |

The sum of i.i.d. random variables - 3,644 | Stacked regression - 2,036 |

USPS dataset - 3,379 | The random model of uncertainty - 1,997 |

Foundations of probability - 2,729 | Normal distribution: the scalar case - 1,920 |

Bias and variance of $\hat \mu$ - 2,690 | Bias and variance - 1,914 |

Bias/variance decomposition of MSE - 2,546 | Classification and Regression Trees - 1,868 |

Stastistical machine learning - 2,518 | Outline - 1,865 |

Axiomatic definition of probability - 2,407 | Sample average - 1,861 |

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