# Statistical foundations of machine learning

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## Table of contents

## Recently updated pages

The PRESS statistic -
29 Oct 2015

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

## Statistics : Total views

Statistical foundations of machine learning - 11,083 | Bias of the estimator $\hat \sigma^2$ - 2,650 |

Introduction - 4,283 | Plug-in principle to define an estimator - 2,561 |

The sum of i.i.d. random variables - 4,192 | Bivariate normal distribution - 2,540 |

Modelling from data - 4,028 | Stacked regression - 2,240 |

USPS dataset - 3,839 | The random model of uncertainty - 2,168 |

Bias/variance decomposition of MSE - 3,074 | Bias and variance - 2,121 |

Bias and variance of $\hat \mu$ - 3,003 | Normal distribution: the scalar case - 2,103 |

Foundations of probability - 2,928 | Sample average - 2,080 |

Axiomatic definition of probability - 2,901 | Classification and Regression Trees - 2,074 |

Stastistical machine learning - 2,687 | Recursive least-squares - 2,035 |

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