# 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 - 9,923 | Bias of the estimator $\hat \sigma^2$ - 2,084 |

Introduction - 3,904 | Plug-in principle to define an estimator - 1,947 |

Modelling from data - 3,622 | Bivariate normal distribution - 1,921 |

The sum of i.i.d. random variables - 3,167 | The random model of uncertainty - 1,873 |

USPS dataset - 3,019 | Stacked regression - 1,861 |

Foundations of probability - 2,596 | Outline - 1,764 |

Bias and variance of $\hat \mu$ - 2,441 | Bias and variance - 1,757 |

Stastistical machine learning - 2,398 | Normal distribution: the scalar case - 1,750 |

Bias/variance decomposition of MSE - 2,172 | Classification and Regression Trees - 1,736 |

Axiomatic definition of probability - 2,109 | Classical parametric estimation - 1,714 |

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