External module "ml/incr/kmeans/docs/types/index.d"

Export assignment incrkmeans

• incrkmeans(k: number | ndarray, ndims: number, options?: Options): Accumulator

• Returns an accumulator function which incrementally partitions data into k clusters.

  throws

  must provide valid options

  throws

  when using sampling to generate initial centroids, the sample size must be greater than or equal to the number of clusters

  Parameters

  • k: number | ndarray

    number of clusters or a k x ndims matrix containing initial centroids

  • ndims: number

    number of dimensions (should only be provided if provided a numeric k argument)

  • Optional options: Options

    function options

  Returns Accumulator

  accumulator function

  Example

  var Float64Array = require( `@stdlib/array/float64` );
  var ndarray = require( `@stdlib/ndarray/ctor` );
  
  // Define initial centroid locations:
  var buffer = [
      0.0, 0.0,
      1.0, 1.0,
      1.0, -1.0,
      -1.0, -1.0,
      -1.0, 1.0
  ];
  var shape = [ 5, 2 ];
  var strides = [ 2, 1 ];
  var offset = 0;
  var order = 'row-major';
  
  var centroids = ndarray( 'float64', buffer, shape, strides, offset, order );
  
  // Create a k-means accumulator:
  var accumulator = incrkmeans( centroids );
  
  var out = accumulator();
  // returns {...}
  
  // Create a data vector:
  buffer = new Float64Array( 2 );
  shape = [ 2 ];
  strides = [ 1 ];
  
  var vec = ndarray( 'float64', buffer, shape, strides, offset, order );
  
  // Provide data to the accumulator:
  vec.set( 0, 2.0 );
  vec.set( 1, 1.0 );
  
  out = accumulator( vec );
  // returns {...}
  
  vec.set( 0, -5.0 );
  vec.set( 1, 3.14 );
  
  out = accumulator( vec );
  // returns {...}
  
  // Retrieve the current cluster results:
  out = accumulator();
  // returns {...}