errors: Calculate Continuous Values Errors

In laresbernardo/lares: Analytics & Machine Learning Sidekick

Calculate Continuous Values Errors

Description

This function lets the user calculate all errors and R squared simultaneously.

This function lets the user calculate Root Mean Squared Error

This function lets the user calculate Mean Absolute Error

This function lets the user calculate Mean Squared Error

This function lets the user calculate Mean Squared Error

This function lets the user calculate R Squared

This function lets the user calculate Adjusted R Squared

Usage

errors(tag, score)

rmse(tag, score)

mae(tag, score)

mse(tag, score)

mape(tag, score)

rsq(tag, score)

rsqa(tag, score)

Arguments

tag	Vector. Real known label
score	Vector. Predicted value or model's result

Value

data.frame or numeric values results for multiple error metrics on continuous numerical vectors inputs.

See Also

Other Model metrics: ROC(), conf_mat(), gain_lift(), loglossBinary(), model_metrics()

Examples

data(dfr) # Results for AutoML Predictions
head(dfr$regr)
df <- errors(dfr$regr$tag, dfr$regr$score)
head(df)

laresbernardo/lares documentation built on April 25, 2024, 5:31 a.m.