0 R Squared

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R^2 (coefficient of determination) regression score function.

Best possible score is 1.0 and it can be negative (because themodel can be arbitrarily worse). A constant model that alwayspredicts the expected value of y, disregarding the input features,would get a R^2 score of 0.0.

Read more in the User Guide.

There are at least two reasons for predicted R-square is equal to 0 (it may even be negative). The fist one is when you have unsignificant effects in your model because if you maintain an. R-square value gives the measure of how much variance is explained by model. For a given set of points, the default regression line with minimum sum of square is the horizontal line that passes. R-squared, also known as the coefficient of determination, is the statistical measurement of the correlation between an investment’s performance and a specific benchmark index. In other words, it shows what degree a stock or portfolio’s performance can be attributed to a benchmark index.

R-squared values range from 0 to 1 and are commonly stated as percentages from 0% to 100%. An R-squared of 100% means that all movements of a security (or another dependent variable) are completely. R-squared is always between 0 and 100%: 0% indicates that the model explains none of the variability of the response data around its mean. 100% indicates that the model explains all the.

Parameters
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y_truearray-like of shape (n_samples,) or (n_samples, n_outputs)

Ground truth (correct) target values.

y_predarray-like of shape (n_samples,) or (n_samples, n_outputs)

Estimated target values.

sample_weightarray-like of shape (n_samples,), default=None

Sample weights.

multioutput{‘raw_values’, ‘uniform_average’, ‘variance_weighted’}, array-like of shape (n_outputs,) or None, default=’uniform_average’

Defines aggregating of multiple output scores.Array-like value defines weights used to average scores.Default is “uniform_average”.

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‘raw_values’ :

Returns a full set of scores in case of multioutput input.

‘uniform_average’ :

Scores of all outputs are averaged with uniform weight.

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‘variance_weighted’ :

Scores of all outputs are averaged, weighted by the variancesof each individual output.

Changed in version 0.19: Default value of multioutput is ‘uniform_average’.

Returns

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zfloat or ndarray of floats

The R^2 score or ndarray of scores if ‘multioutput’ is‘raw_values’.

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Notes

This is not a symmetric function.

Unlike most other scores, R^2 score may be negative (it need not actuallybe the square of a quantity R).

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This metric is not well-defined for single samples and will return a NaNvalue if n_samples is less than two.

References

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Zero R Squared

Examples