feat: add nGMCA

README.md

@@ -70,6 +70,7 @@ It will be available as the global `ML` variable. The package is in UMD format.
 - Similarity functions: [`ML.Similarity`](https://github.com/mljs/distance)
 - Distance matrix: [`ML.distanceMatrix`](https://github.com/mljs/distance-matrix)
 - XORShift-add RNG: [`ML.XSadd`](https://github.com/mljs/xsadd)
+- non-negative Generalized Morphological Component Analysis [`ML.nGMCA`](https://github.com/mljs/nGMCA)
 
 ### [`ML.Array`](https://github.com/mljs/array)
 

package.json

@@ -74,6 +74,7 @@
  "ml-levenberg-marquardt": "^2.1.1",
  "ml-matrix": "^6.5.1",
  "ml-naivebayes": "^4.0.0",
+ "ml-ngmca": "^0.1.2",
  "ml-pad-array": "^2.0.0",
  "ml-pca": "^4.0.1",
  "ml-performance": "^0.2.0",

src/index.js

@@ -1,7 +1,7 @@
 import { DecisionTreeClassifier, DecisionTreeRegression } from "ml-cart";
 import {
  RandomForestClassifier,
- RandomForestRegression
+ RandomForestRegression,
 } from "ml-random-forest";
 
 // Try to keep this list in the same structure as the README.
@@ -35,7 +35,7 @@ export {
  PowerRegression,
  ExponentialRegression,
  TheilSenRegression,
- RobustPolynomialRegression
+ RobustPolynomialRegression,
 } from "ml-regression";
 export { DecisionTreeRegression };
 export { RandomForestRegression };
@@ -53,7 +53,7 @@ const {
  EVD,
  CholeskyDecomposition,
  LuDecomposition,
- QrDecomposition
+ QrDecomposition,
 } = MatrixLib;
 export {
  MatrixLib,
@@ -62,7 +62,7 @@ export {
  EVD,
  CholeskyDecomposition,
  LuDecomposition,
- QrDecomposition
+ QrDecomposition,
 };
 
 export { SparseMatrix } from "ml-sparse-matrix";
@@ -71,6 +71,7 @@ import { distance, similarity } from "ml-distance";
 export { distance as Distance, similarity as Similarity };
 export { default as distanceMatrix } from "ml-distance-matrix";
 export { default as XSadd } from "ml-xsadd";
+export { nGMCA } from "ml-ngmca";
 
 // Statistics
 export { default as Performance } from "ml-performance";
@@ -111,7 +112,7 @@ export const Array = {
  sequentialFill,
  standardDeviation,
  sum,
- variance
+ variance,
 };
 
 import centroidsMerge from "ml-array-xy-centroids-merge";
@@ -134,5 +135,5 @@ export const ArrayXY = {
  uniqueX,
  weightedMerge,
  equallySpaced,
- filterX
+ filterX,
 };