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
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
