Tags: machine learning, statistics |

Shared by: joubin |

Created on: Jun 10 2017 (Sat) @ 03:32 PM |

RSS: Residual Sum of Squares It is a measure of the discrepancy between the data and an estimation model. A small RSS indicates a tight fit of the model to the data. It is used as an optimality criterion in parameter selection and model selection. RSS is the sum of the squares of residuals (deviations predicted from actual empirical values of data). In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "theoretical value". Residual of an observed value is the difference between the observed value and the estimated value of the quantity of interest. |

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