make_feature_from_data_frame {PrInCE} | R Documentation

## Create a feature vector for a classifier from a data frame

### Description

Convert a data frame containing pairwise interactions, and a score or other data associated with each interaction, into a feature vector that matches the dimensions of a data frame used as input to a classifier, such as a naive Bayes, random forests, or support vector machine classifier.

### Usage

    make_feature_from_data_frame(dat, target, dat_node_cols = c(1, 2),
      target_node_cols = c(1, 2), feature_col = 3, default_value = NA)

### Arguments

`dat` | a data frame containing pairwise interactions and a feature to be converted to a vector in a third column
`target` | the data frame of features that will be provided as input to a classifier
`dat_node_cols` | a vector of length two, denoting either the indices (integer vector) or column names (character vector) of the columns within the feature data frame; defaults to the first two columns of the data frame (`c(1, 2)`)
`target_node_cols` | a vector of length two, denoting either the indices (integer vector) or column names (character vector) of the columns within the target data frame; defaults to the first two columns of the data frame (`c(1, 2)`)
`feature_col` | the name or index of the column in the first data frame that contains a feature for each interaction
`default_value` | the default value for protein pairs that are not in the first data frame (set, by default, to `NA`)

### Value

a vector matching the dimensions and order of the feature data frame, to use as input for a classifier in interaction prediction

[Package PrInCE version 1.0.1 Index]