Views of a multidimensional dataset, ranked by their prediction power, non-Shiny version.

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Description

findviews_to_predict_core detects groups of mutually dependent columns, and ranks them by their predictive power. It produces the same results as findviews_to_predict, but does not present them with a Shiny app.

Usage

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findviews_to_predict_core(target, data, view_size_max = NULL,
  clust_method = "complete")

Arguments

target

Name of the variable to be predicted.

data

Data frame or matrix to be processed

view_size_max

Maximum number of columns in the views. If set to NULL, findviews uses log2(ncol(data)), rounded upwards and capped at 5.

clust_method

Character describing a clustering method, used internally by hclust. Example values are "complete", "single" or "average".

Details

The function findviews_to_predict_core takes a data set and a target variable as input. It detects clusters of statistically dependent columns in the data set - e.g., views - and ranks those groups according to how well they predict the target variable. See the documentation of findviews_to_predict for more details.

The difference between findviews_to_predict and findviews_to_predict_core is that the former presents its results with a Shiny app, while the latter simply outputs them as R stuctures.

Examples

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