hpc_cv: Multiclass Probability Predictions

In yardstick: Tidy Characterizations of Model Performance

Multiclass Probability Predictions

Description

Multiclass Probability Predictions

Details

This data frame contains the predicted classes and class probabilities for a linear discriminant analysis model fit to the HPC data set from Kuhn and Johnson (2013). These data are the assessment sets from a 10-fold cross-validation scheme. The data column columns for the true class (obs), the class prediction (pred) and columns for each class probability (columns VF, F, M, and L). Additionally, a column for the resample indicator is included.

Value

hpc_cv

a data frame

Source

Kuhn, M., Johnson, K. (2013) Applied Predictive Modeling, Springer

Examples

data(hpc_cv)
str(hpc_cv)

# `obs` is a 4 level factor. The first level is `"VF"`, which is the
# "event of interest" by default in yardstick. See the Relevant Level
# section in any classification function (such as `?pr_auc`) to see how
# to change this.
levels(hpc_cv$obs)

yardstick documentation built on June 22, 2024, 7:07 p.m.