Creates co-occurrence matrix from training trials — create_cooc

Given a training order (list of words and objects per trial), this function returns a matrix tallying word-object co-occurrences across the trials. This matrix can be used to analyze the frequency with which certain words and objects appear together during the training phase.

Usage

create_cooc_matrix(train)

Arguments

train: A list representing the training data, where each element is a trial that includes both words and objects. The structure is expected to have sub-elements words and objects for each trial.

Value

A matrix where each element represents the count of co-occurrences between a word (rows) and an object (columns). The row and column names correspond to the unique words and objects found in the training data, respectively.

Examples

create_cooc_matrix(xsl_datasets[[1]]$train)
#>    1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
#> 1  6 1 2 1 1 0 0 2 2  2  1  1  1  1  0  1  0  2
#> 2  0 6 2 3 1 0 2 1 0  1  1  1  1  0  1  1  2  1
#> 3  3 2 6 0 1 1 0 2 0  1  0  2  0  0  1  1  1  3
#> 4  0 3 2 6 1 1 0 1 1  1  1  0  2  2  0  1  2  0
#> 5  2 0 1 0 6 2 0 2 2  1  0  3  0  1  2  1  1  0
#> 6  0 0 2 1 2 6 1 1 2  3  1  1  1  0  0  2  0  1
#> 7  0 0 0 1 0 1 6 2 0  2  2  3  2  0  1  0  2  2
#> 8  1 1 1 1 1 1 2 6 1  1  0  1  2  2  2  0  0  1
#> 9  1 0 1 1 2 2 0 1 6  1  1  0  0  2  1  2  1  2
#> 10 2 2 2 1 1 2 1 0 2  6  0  2  2  1  0  0  0  0
#> 11 1 2 0 1 0 1 2 0 1  0  6  1  1  1  1  3  2  1
#> 12 2 0 1 0 3 0 2 2 1  1  1  6  1  0  2  0  2  0
#> 13 1 0 0 1 1 1 2 1 1  3  2  1  6  1  1  0  1  1
#> 14 1 1 0 2 0 1 0 1 2  1  2  0  1  6  1  3  1  1
#> 15 2 1 1 0 2 2 1 1 0  0  0  1  1  2  6  1  2  1
#> 16 1 2 1 1 1 2 1 1 1  0  2  0  1  2  1  6  0  1
#> 17 0 2 0 3 1 0 2 0 1  0  2  0  1  2  3  0  6  1
#> 18 1 1 2 1 0 1 2 0 1  0  2  1  1  1  1  2  1  6