- overfit
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adj.
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Universalium. 2010.
overfit
Look at other dictionaries:
overfit — verb To use a statistical model that has too many parameters relative to the size of the sample leading to a good fit with the sample data but a poor fit with new data … Wiktionary
overfit — o′ver•fit′ adj … From formal English to slang
overfit — /oʊvəˈfɪt/ (say ohvuh fit) adjective at a level of fitness that is excessive …
overfit — adj … Useful english dictionary
Overfitting — Noisy (roughly linear) data is fitted to both linear and polynomial functions. Although the polynomial function passes through each data point, and the linear function through few, the linear version is a better fit. If the regression curves were … Wikipedia
Bootstrap aggregating — (bagging) is a meta algorithm to improve machine learning of classification and regression models in terms of stability and classification accuracy. It also reduces variance and helps to avoid overfitting. Although it is usually applied to… … Wikipedia
Multivariate adaptive regression splines — (MARS) is a form of regression analysis introduced by Jerome Friedman in 1991.[1] It is a non parametric regression technique and can be seen as an extension of linear models that automatically models non linearities and interactions. The term… … Wikipedia
Multifactor dimensionality reduction — (MDR) is a data mining approach for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. MDR was designed specifically to identify interactions among discrete… … Wikipedia
Computational phylogenetics — is the application of computational algorithms, methods and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other taxa. For… … Wikipedia
Local regression — LOESS, or locally weighted scatterplot smoothing, is one of many modern modeling methods that build on classical methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which … Wikipedia
