multivarious (version 0.3.1)

classifier.multiblock_biprojector: Multiblock Bi-Projector Classifier

Description

Constructs a k-Nearest Neighbors (k-NN) classifier based on a fitted multiblock_biprojector model object. The classifier uses the projected scores as the feature space for k-NN.

Usage

# S3 method for multiblock_biprojector
classifier(
  x,
  colind = NULL,
  labels,
  new_data = NULL,
  block = NULL,
  global_scores = TRUE,
  knn = 1,
  ...
)

Value

An object of class multiblock_classifier, which also inherits from classifier.

Arguments

x

A fitted multiblock_biprojector object.

colind

An optional numeric vector specifying column indices from the original data space. If provided when global_scores=FALSE, these indices are used to perform a partial projection for the reference scores. If provided when global_scores=TRUE, this value is stored but does not affect the reference scores (which remain global); however, it may influence the default projection behavior during prediction unless overridden there. See predict.classifier.

labels

A factor or vector of class labels for the training data.

new_data

An optional data matrix used to generate reference scores when global_scores=FALSE, or when global_scores=TRUE but colind or block is also provided (overriding global_scores). Must be provided if global_scores=FALSE.

block

An optional integer specifying a predefined block index. Used for partial projection if global_scores=FALSE or if new_data is also provided. Cannot be used simultaneously with colind.

global_scores

Logical. DEPRECATED This argument is deprecated and its behavior has changed. Reference scores are now determined automatically:

• If new_data is NULL: Uses the globally projected scores stored in x (scores(x)).

• If new_data is provided: Always projects new_data to generate reference scores (using partial_project/project_block if colind/block are given, project otherwise).

knn

The integer number of nearest neighbors (k) for the k-NN algorithm (default: 1).

...

Additional arguments (currently ignored).

Details

Users can specify whether to use the globally projected scores stored within the model (global_scores = TRUE) or to generate reference scores by projecting provided new_data (global_scores = FALSE). Partial projections based on colind or block can be used when global_scores = FALSE or when new_data is provided alongside colind/block. Prediction behavior is further controlled by arguments passed to predict.classifier.

See Also

Other classifier: classifier(), rf_classifier.projector()