@saehrimnir/druidjs / LDA
Class: LDA<T>
Defined in: dimred/LDA.js:20
Linear Discriminant Analysis (LDA)
A supervised dimensionality reduction technique that finds the axes that maximize the separation between multiple classes.
Template
T
Extends
DR
Type Parameters
| Type Parameter | Description |
|---|---|
T extends InputType |
Constructors
Constructor
new LDA<T>(X: T, parameters: Partial<ParametersLDA> & {
labels: any[] | Float64Array<ArrayBufferLike>;
}): LDA<T>;Defined in: dimred/LDA.js:28
Linear Discriminant Analysis.
Parameters
| Parameter | Type | Description |
|---|---|---|
X | T | The high-dimensional data. |
parameters | Partial<ParametersLDA> & { labels: any[] | Float64Array<ArrayBufferLike>; } | Object containing parameterization of the DR method. |
Returns
LDA<T>
See
https://onlinelibrary.wiley.com/doi/10.1111/j.1469-1809.1936.tb02137.x
Overrides
DR.constructorProperties
| Property | Type | Inherited from | Defined in |
|---|---|---|---|
__input | T | DR.__input | dimred/DR.js:46 |
_D | number | DR._D | dimred/DR.js:28 |
_is_initialized | boolean | DR._is_initialized | dimred/DR.js:34 |
_N | number | DR._N | dimred/DR.js:30 |
_parameters | ParametersLDA | DR._parameters | dimred/DR.js:49 |
_randomizer | Randomizer | DR._randomizer | dimred/DR.js:32 |
_type | "array" | "matrix" | "typed" | DR._type | dimred/DR.js:54 |
X | Matrix | DR.X | dimred/DR.js:56 |
Y | Matrix | DR.Y | dimred/DR.js:58 |
Accessors
projection
Get Signature
get projection(): T;Defined in: dimred/DR.js:219
Returns
T
The projection in the type of input X.
Inherited from
DR.projectionMethods
[dispose]()
dispose: void;Defined in: dimred/DR.js:320
Alias of release for the using declaration, so a hand-driven run frees its buffers when the block exits. Note that transform and a completed or break-ed generator() already release on their own — this only matters for a generator abandoned part way.
using tsne = new TSNE(X, { d: 2 });
const steps = tsne.generator(500);
steps.next(); // buffers released when the enclosing block exitsReturns
void
Inherited from
DR.[dispose]check_init()
check_init(): DR<T, ParametersLDA>;Defined in: dimred/DR.js:210
If the respective DR method has an init function, call it before transform.
Returns
DR<T, ParametersLDA>
Inherited from
DR.check_initgenerator()
generator(): Generator<T, T, void>;Defined in: dimred/LDA.js:41
Transforms the inputdata X to dimensionality d.
Returns
Generator<T, T, void>
A generator yielding the intermediate steps of the projection.
Overrides
DR.generatorinit()
abstract init(...args: unknown[]): void;Defined in: dimred/DR.js:201
Parameters
| Parameter | Type | Description |
|---|---|---|
...args | unknown[] | - |
Returns
void
Inherited from
DR.initparameter()
Call Signature
parameter(): ParametersLDA;Defined in: dimred/DR.js:82
Get all Parameters.
Returns
Inherited from
DR.parameterCall Signature
parameter<K>(name: K): ParametersLDA[K];Defined in: dimred/DR.js:88
Get value of given parameter.
Type Parameters
| Type Parameter | Description |
|---|---|
K extends keyof ParametersLDA |
Parameters
| Parameter | Type | Description |
|---|---|---|
name | K | Name of the parameter. |
Returns
Inherited from
DR.parameterCall Signature
parameter<K>(name: K, value: ParametersLDA[K]): LDA<T>;Defined in: dimred/DR.js:95
Set value of given parameter.
Type Parameters
| Type Parameter | Description |
|---|---|
K extends keyof ParametersLDA |
Parameters
| Parameter | Type | Description |
|---|---|---|
name | K | Name of the parameter. |
value | ParametersLDA[K] | Value of the parameter to set. |
Returns
LDA<T>
Inherited from
DR.parameterrelease()
release(): LDA<T>;Defined in: dimred/DR.js:302
Hands back the WASM buffers this instance is holding.
Only needed after driving generator() by hand and stopping early — a plain transform(), or a for…of over generator() (including one you break), already releases when it ends. It frees only this method's buffers, never another running instance's, and the next run simply reallocates, so it is safe to call at any time, more than once, and while other instances are mid-run.
Returns
LDA<T>
Example
const tsne = new TSNE(X, { d: 2 });
const steps = tsne.generator(500);
steps.next();
tsne.release(); // stop early and give the buffers backInherited from
DR.releasetransform()
transform(): T;Defined in: dimred/LDA.js:51
Transforms the inputdata X to dimensionality d.
Returns
T
- The projected data.
Overrides
DR.transformtransform_async()
transform_async(...args: unknown[]): Promise<T>;Defined in: dimred/DR.js:241
Computes the projection.
Parameters
| Parameter | Type | Description |
|---|---|---|
...args | unknown[] | Arguments the transform method of the respective DR method takes. |
Returns
Promise<T>
The dimensionality reduced dataset.
Inherited from
DR.transform_asyncgenerator()
static generator<T, Para>(X: T, parameters: Para): Generator<T, T, void>;Defined in: dimred/LDA.js:137
Type Parameters
| Type Parameter | Description |
|---|---|
T extends InputType | |
Para extends { seed?: number; } |
Parameters
| Parameter | Type | Description |
|---|---|---|
X | T | - |
parameters | Para | - |
Returns
Generator<T, T, void>
Overrides
DR.generatortransform()
static transform<T, Para>(X: T, parameters: Para): T;Defined in: dimred/LDA.js:124
Type Parameters
| Type Parameter | Description |
|---|---|
T extends InputType | |
Para extends { seed?: number; } |
Parameters
| Parameter | Type | Description |
|---|---|---|
X | T | - |
parameters | Para | - |
Returns
T
Overrides
DR.transformtransform_async()
static transform_async<T, Para>(X: T, parameters: Para): Promise<T>;Defined in: dimred/LDA.js:151
Type Parameters
| Type Parameter | Description |
|---|---|
T extends InputType | |
Para extends { seed?: number; } |
Parameters
| Parameter | Type | Description |
|---|---|---|
X | T | - |
parameters | Para | - |
Returns
Promise<T>
Overrides
DR.transform_async