rsquared¶

getml.pipeline.scores.rsquared = 'rsquared'¶

$R^{2}$ - squared correlation coeefficient between predictions and targets.

Used for regression problems.

$R^{2}$ is defined as follows:

$R^{2} = \frac{(\sum_{i=1}^n ( y_i - \bar{y_i} ) * ( \hat{y_i} - \bar{\hat{y_i}} ))^2 }{\sum_{i=1}^n ( y_i - \bar{y_i} )^2 \sum_{i=1}^n ( \hat{y_i} - \bar{\hat{y_i}} )^2 },$

where $y_i$ are the true values, $\hat{y_i}$ are the predictions and $\bar{...}$ denotes the mean operator.

An $R^{2}$ of 1 implies perfect correlation between the predictions and the targets and an $R^{2}$ of 0 implies no correlation at all.