• Default of print_eval is TRUE when data_test is supplied.
  • covid_train and covid_test datasets are pre-processed.
  • add option to show target legend

Bug fixes: * requires custom tree to be trained on dataset with dependent variable as factor when task is classification. * label_map works again * fix mismatching categories in tree vs heatmap

Significant changes: * data argument is now replaced with x, which can be a dataframe (or tibble), a party (or constparty) object specifying the precomputed tree, or partynode object specifying the customized tree. custom_tree argument is no longer needed. * treeheatr() is now an alias for heat_tree()

Others: * include the diabetes dataset * reduce legend margin * remove my_target as column names within functions * allow wrapping as.party() around rpart object * use ARSA as seriation method for samples * swap the position of two arguments: target_lab and data_test * allow the user to choose features to show in the heatmap

ANNOUNCEMENTS

  • treeheatr 0.1.0 - first CRAN release!