API Reference - Models - NearestCentroid

Stored Model Parameters

Contains a table of matrices.

  • ModelParameters[1]: meanMatrix

  • ModelParameters[2]: numberOfDataPointVector

Constructors

new()

Create new model object. If any of the arguments are nil, default argument values for that argument will be used.

NearestCentroid.new(distanceFunction: string, use, useWeightedDistance: boolean: ModelObject

Parameters:

  • distanceFunction: The distance function to be used to measure the similarity between two data points. Available options are:

    • Euclidean (Default)

    • Manhattan

    • Cosine

Returns:

  • ModelObject: The generated model object.

Functions

train()

Train the model.

NearestCentroid:train(featureMatrix: Matrix, labelVector: Matrix): number[]

Parameters:

  • featureMatrix: Matrix containing all data.

  • labelVector: A (n x 1) matrix containing values related to featureMatrix.

Returns:

  • costArray: An array containing cost values.

predict()

Predict the values for given data.

NearestCentroid:predict(featureMatrix: Matrix, returnOriginalOutput: boolean): Matrix, Matrix -OR- Matrix

Parameters

  • featureMatrix: Matrix containing all data.

  • returnOriginalOutput: Set whether or not to return predicted matrix instead of value with highest probability.

Returns:

  • predictedlabelVector: A vector tcontaining predicted labels generated from the model.

  • valueVector: A vector that contains the values of predicted labels.

-OR-

  • predictedMatrix: A matrix containing all distances between stored and given data points.

Inherited From