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.

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"
)

Arguments

name	(Optional) String name of the metric instance.
dtype	(Optional) Data type of the metric result. Defaults to `tf$float32`.
...	additional arguments to pass
multioutput	one of the following: "raw_values", "uniform_average", "variance_weighted"

Value

r squared score: float

Examples

if (FALSE) {

actuals = tf$constant(c(1, 4, 3), dtype=tf$float32)
preds = tf$constant(c(2, 4, 4), dtype=tf$float32)
result = metric_rsquare()
result$update_state(actuals, preds)
paste('R^2 score is: ', r1$result()$numpy()) # 0.57142866

}