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snowflake.ml.modeling.metrics.r2_score¶

snowflake.ml.modeling.metrics.r2_score(*, df: DataFrame, y_true_col_name: str, y_pred_col_name: str) → float¶

$R^2$ (coefficient of determination) regression score function. Returns R squared metric on 2 columns in the dataframe.

Best possible score is 1.0 and it can be negative (because the model can be arbitrarily worse). In the general case when the true y is non-constant, a constant model that always predicts the average y disregarding the input features would get a $R^2$ score of 0.0.

Args:

df: snowpark.DataFrame: Input dataframe.
y_true_col_name: string: Column name representing actual values.
y_pred_col_name: string: Column name representing predicted values.

Returns:

R squared metric.