Calculate and plot a multi-class model's predictions accuracy based on top N predictions and distribution of probabilities.
Arguments
- tag
Vector. Real known label.
- score
Vector. Predicted value or model's result.
- multis
Data.frame. Containing columns with each category probability or score (only used when more than 2 categories coexist).
- model_name
Character. Model's name
See also
Other ML Visualization:
mplot_conf()
,
mplot_cuts_error()
,
mplot_cuts()
,
mplot_density()
,
mplot_full()
,
mplot_gain()
,
mplot_importance()
,
mplot_lineal()
,
mplot_metrics()
,
mplot_response()
,
mplot_roc()
,
mplot_splits()
Examples
Sys.unsetenv("LARES_FONT") # Temporal
data(dfr) # Results for AutoML Predictions
mplot_topcats(dfr$class3$tag, dfr$class3$score,
multis = subset(dfr$class3, select = -c(tag, score)),
model_name = "Titanic Class Model"
)