Class: LDA

new LDA(X, parameters)

Linear Discriminant Analysis.

Parameters:

Name Type Description

X

Matrix

The high-dimensional data.

parameters

object

Object containing parameterization of the DR method.

Properties

Name	Type	Attributes	Default	Description
`labels`	Array.<any>			The labels / classes for each data point.
`d`	number	<optional>	2	The dimensionality of the projection.
`seed`	number	<optional>	1212	the seed for the random number generator.
`eig_args`	object	<optional>		Parameters for the eigendecomposition algorithm.

Source: dimred/LDA.js, line 10
See: https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1936.tb02137.x

Extends

Members

projection

Overrides: DR#projection
Source: dimred/DR.js, line 112

Methods

check_init() → {DR}

If the respective DR method has an init function, call it before transform.

Overrides: DR#check_init
Source: dimred/DR.js, line 101

Returns:

Type:: DR

(generator) generator() → {Matrix|Array.<Array.<number>>}

Computes the projection.

Overrides: DR#generator
Source: dimred/DR.js, line 93

Yields:

the intermediate steps of the projection.

Type:: Matrix | Array.<Array.<number>>

parameter(nameopt, valueopt) → {DR|any|object}

Set and get parameters

Parameters:

Name	Type	Attributes	Default	Description
`name`	string	<optional>	null	Name of the parameter. If not given then returns all parameters as an Object.
`value`	any	<optional>	null	Value of the parameter to set. If `name` is set and `value` is not given, returns the value of the respective parameter.

Overrides: DR#parameter
Source: dimred/DR.js, line 56

Returns:

On setting a parameter, this function returns the DR object. If name is set and value == null then return actual parameter value. If name is not given, then returns all parameters as an Object.

Type:: DR | any | object

Example

'''
const DR = new druid.TSNE(X, {d: 3}); // creates a new DR object, with parameter for <code>d</code> = 3.
DR.parameter("d"); // returns 3,
DR.parameter("d", 2); // sets parameter <code>d</code> to 2 and returns <code>DR</code>.
'''

transform()

Transforms the inputdata X to dimenionality d.

Overrides: DR#transform
Source: dimred/LDA.js, line 35

(async) transform_async(…args) → {Promise.<(Matrix|Array.<Array.<number>>)>}

Computes the projection.

Parameters:

Name	Type	Attributes	Description
`args`	unknown	<repeatable>	Arguments the transform method of the respective DR method takes.

Overrides: DR#transform_async
Source: dimred/DR.js, line 126

Returns:

the dimensionality reduced dataset.

Type:: Promise.<(Matrix|Array.<Array.<number>>)>