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overfit

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The answer OVERFIT has 0 possible clue(s) in existing crosswords.

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Definitions of overfit in various dictionaries:

adj - fitted to excess

OVERFIT - In statistics, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore f...

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Possible Dictionary Clues
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.

Overfit might refer to
In statistics, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably". An overfitted model is a statistical model that contains more parameters than can be justified by the data. The essence of overfitting is to have unknowingly extracted some of the residual variation (i.e. the noise) as if that variation represented underlying model structure.Underfitting occurs when a statistical model cannot adequately capture the underlying structure of the data. An underfitted model is a model where some parameters or terms that would appear in a correctly specified model are missing. Underfitting would occur, for example, when fitting a linear model to non-linear data. Such a model will tend to have poor predictive performance. * Overfitting and underfitting can occur in machine learning, in particular. In machine learning, the phenomena are sometimes c

Overfit might refer to

In statistics, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably". An overfitted model is a statistical model that contains more parameters than can be justified by the data. The essence of overfitting is to have unknowingly extracted some of the residual variation (i.e. the noise) as if that variation represented underlying model structure.Underfitting occurs when a statistical model cannot adequately capture the underlying structure of the data. An underfitted model is a model where some parameters or terms that would appear in a correctly specified model are missing. Underfitting would occur, for example, when fitting a linear model to non-linear data. Such a model will tend to have poor predictive performance.
* Overfitting and underfitting can occur in machine learning, in particular. In machine learning, the phenomena are sometimes c

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