metric_rsquare | R Documentation |
RSquare
This is also called as coefficient of determination. It tells how close are data to the fitted regression line. Highest score can be 1.0 and it indicates that the predictors perfectly accounts for variation in the target. Score 0.0 indicates that the predictors do not account for variation in the target. It can also be negative if the model is worse.
metric_rsquare( name = "r_square", dtype = tf$float32, multioutput = "uniform_average", y_shape = 1, ... )
name |
(Optional) String name of the metric instance. |
dtype |
(Optional) Data type of the metric result. Defaults to 'tf$float32'. |
multioutput |
one of the following: "raw_values", "uniform_average", "variance_weighted" |
y_shape |
output tensor shape |
... |
additional arguments to pass |
r squared score: float
## Not run: actuals = tf$constant(c(1, 4, 3), dtype=tf$float32) preds = tf$constant(c(2, 4, 4), dtype=tf$float32) result = metric_rsquare() result$update_state(actuals, preds) paste('R^2 score is: ', result$result()$numpy()) # 0.57142866 ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.