# rsquared¶

getml.pipeline.metrics.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.