Package index • nuggets

Data Preparation

Functions for transformation of input data into the format suitable for pattern extraction.

partition(): Convert columns of data frame to Boolean or fuzzy sets

remove_almost_constant(): Remove almost constant columns from a data frame

Pre-defined Pattern Extraction

Functions for extraction of pre-defined patterns from input data.

dig_associations() experimental: Search for association rules

dig_correlations() experimental: Search for conditional correlations

dig_baseline_contrasts() experimental: Search for conditions that yield in statistically significant one-sample test in selected variables.

dig_complement_contrasts() experimental: Search for conditions that provide significant differences in selected variables to the rest of the data table

dig_paired_baseline_contrasts() experimental: Search for conditions that provide significant differences between paired variables

Custom Pattern Extraction

Functions for extraction of custom patterns from input data.

dig() experimental: Search for patterns of custom type

dig_grid() experimental: Search for grid-based rules

Tools and Helper Functions

Other functions that can be useful in the pattern extraction process.

format_condition(): Format a vector of predicates into a string with a condition

is_almost_constant(): Tests if almost all values in a vector are the same.

is_degree(): Tests whether the given argument is a numeric value from the interval \([0,1]\)

is_subset(): Determine whether the first vector is a subset of the second vector

var_grid(): Create a tibble of combinations of selected column names

var_names(): Extract variable names from predicates

which_antichain(): Return indices of first elements of the list, which are incomparable with preceding elements.