hpc_cv dataset

Multiclass Probability Predictions

Multiclass Probability Predictions

Source

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

Returns

  • hpc_cv: a data frame

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.

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)
  • Maintainer: Emil Hvitfeldt
  • License: MIT + file LICENSE
  • Last published: 2025-01-22

About the dataset

  • Number of rows: 3467
  • Number of columns: 7
  • Class: data.frame

Column names and types

  • obs:factor
  • pred:factor
  • VF:numeric
  • F:numeric
  • M:numeric
  • L:numeric
  • Resample:character