mplot_splits | R Documentation |
This function lets us split and compare quantiles on a given prediction to compare different categorical values vs scores grouped by equal sized buckets.
mplot_splits(
tag,
score,
splits = 5,
subtitle = NA,
model_name = NA,
save = FALSE,
subdir = NA,
file_name = "viz_splits.png"
)
tag |
Vector. Real known label. |
score |
Vector. Predicted value or model's result. |
splits |
Integer. Number of separations to plot |
subtitle |
Character. Subtitle to show in plot |
model_name |
Character. Model's name |
save |
Boolean. Save output plot into working directory |
subdir |
Character. Sub directory on which you wish to save the plot |
file_name |
Character. File name as you wish to save the plot |
Plot with distribution and performance results by splits.
Other ML Visualization:
mplot_conf()
,
mplot_cuts()
,
mplot_cuts_error()
,
mplot_density()
,
mplot_full()
,
mplot_gain()
,
mplot_importance()
,
mplot_lineal()
,
mplot_metrics()
,
mplot_response()
,
mplot_roc()
,
mplot_topcats()
Sys.unsetenv("LARES_FONT") # Temporal
data(dfr) # Results for AutoML Predictions
lapply(dfr, head)
# For categorical (binary) values
mplot_splits(dfr$class2$tag, dfr$class2$scores,
splits = 4,
model_name = "Titanic Survived Model"
)
# For categorical (+2) values
mplot_splits(dfr$class3$tag, dfr$class2$scores,
model_name = "Titanic Class Model"
)
# For continuous values
mplot_splits(dfr$regr$tag, dfr$regr$score,
splits = 4,
model_name = "Titanic Fare Model"
)
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