This function takes in a factorized Boolean matrix and generate frequent itemsets that meet all the user provided criteria provided by the calling function.
run_apriori_freqitems(
apriori_input_df,
combo_length,
support_threshold,
input_colname_list,
confidence_threshold = confidence_threshold,
include_output_ind = include_output_ind,
output_colname_list = output_colname_list
)An input factorized Boolean dataframe with multiple input and outcome variables
The length of the combinations specified by the user
Minimum support value calculated based on the minimum absolute observed frequency threshold specified by the user
A list of column names that identify the input variables
Minimum confidence threshold specified by the user
Specifies if the outcome variables must also be made part of the analysis using the algorithm
A list of column names that identify the outcome variables
A list of frequent item sets that meet all the constraints supplied to the apriori algorithm
This is a function leveraged by few of the four main methods available to the users.