| calculate_interval | Calculate interval summaries with a measure of central tendency of classification results | 
| classify | Fit classifiers using time-series features using a resample-based approach and get a fast understanding of performance | 
| cluster | Perform cluster analysis of time series using their feature vectors | 
| compare_features | Conduct statistical testing on time-series feature classification performance to identify top features or compare entire sets | 
| filter_duplicates | Remove duplicate features that exist in multiple feature sets and retain a reproducible random selection of one of them | 
| filter_good_features | Filter resample data sets according to good feature list | 
| find_good_features | Helper function to find features in both train and test set that are "good" | 
| fit_models | Fit classification model and compute key metrics | 
| get_rescale_vals | Calculate central tendency and spread values for all numeric columns in a dataset | 
| interval | Calculate interval summaries with a measure of central tendency of classification results | 
| make_title | Helper function for converting to title case | 
| plot.feature_calculations | Produce a plot for a feature_calculations object | 
| plot.feature_projection | Produce a plot for a feature_projection object | 
| plot.interval_calculations | Produce a plot for a interval_calculations object | 
| project | Project a feature matrix into a two-dimensional representation using PCA, MDS, t-SNE, or UMAP ready for plotting | 
| reduce_dims | Project a feature matrix into a two-dimensional representation using PCA, MDS, t-SNE, or UMAP ready for plotting | 
| resample_data | Helper function to create a resampled dataset | 
| rescale_zscore | Calculate z-score for all columns in a dataset using train set central tendency and spread | 
| select_stat_cols | Helper function to select only the relevant columns for statistical testing | 
| shrink | Use a cross validated penalized maximum likelihood generalized linear model to perform feature selection | 
| stat_test | Calculate p-values for feature sets or features relative to an empirical null or each other using resampled t-tests | 
| theftdlc | Analyse and Interpret Time Series Features | 
| tsfeature_classifier | Fit classifiers using time-series features using a resample-based approach and get a fast understanding of performance |