Refactor model instantiation in some classes to use function references instead of constructor calls.

Author: ishii-norimi

lib/model/ensemble_binary.js

@@ -9,7 +9,7 @@
  */
 export default class EnsembleBinaryModel {
 	/**
-	 * @param {new () => BinaryModel} model Function to generate the model
+	 * @param {() => BinaryModel} model Function to generate the model
 	 * @param {'oneone' | 'onerest'} type Type name
 	 * @param {*[]} [classes] Initial class labels
 	 */
@@ -58,7 +58,7 @@ class OneVsRestModel {
 		if (classes) {
 			this._n = classes.length
 			for (let i = 0; i < this._n; i++) {
-				this._model[i] = new model()
+				this._model[i] = model()
 			}
 		}
 	}
@@ -69,7 +69,7 @@ class OneVsRestModel {
 			this._classes = [...new Set(train_y)]
 			this._n = this._classes.length
 			for (let i = 0; i < this._n; i++) {
-				this._model[i] = new this._modelcls()
+				this._model[i] = this._modelcls()
 			}
 		}
 		for (let i = 0; i < this._n; i++) {
@@ -133,7 +133,7 @@ class OneVsOneModel {
 			for (let i = 0; i < this._n; i++) {
 				this._model[i] = []
 				for (let j = 0; j < i; j++) {
-					this._model[i][j] = new model()
+					this._model[i][j] = model()
 				}
 			}
 		}
@@ -147,7 +147,7 @@ class OneVsOneModel {
 			for (let i = 0; i < this._n; i++) {
 				this._model[i] = []
 				for (let j = 0; j < i; j++) {
-					this._model[i][j] = new this._modelcls()
+					this._model[i][j] = this._modelcls()
 				}
 			}
 		}

lib/model/genetic_algorithm.js

@@ -14,13 +14,13 @@ import { QTableBase } from './q_learning.js'
 class GeneticAlgorithm {
 	/**
 	 * @param {number} size Number of models per generation
-	 * @param {new () => GeneticModel} model Function to generate the model
+	 * @param {() => GeneticModel} model Function to generate the model
 	 */
 	constructor(size, model) {
 		this._size = size
 		this._models = []
 		for (let i = 0; i < size; i++) {
-			this._models.push(new model())
+			this._models.push(model())
 		}
 	}
 

lib/model/probability_based_classifier.js

@@ -8,7 +8,7 @@
  */
 export default class ProbabilityBasedClassifier {
 	/**
-	 * @param {new () => ProbabilityModel} model Function to generate the model
+	 * @param {() => ProbabilityModel} model Function to generate the model
 	 */
 	constructor(model) {
 		this._classes = null
@@ -25,7 +25,7 @@ export default class ProbabilityBasedClassifier {
 		if (!this._classes) {
 			this._classes = [...new Set(y)]
 			for (let i = 0; i < this._classes.length; i++) {
-				this._models[i] = new this._modelcls()
+				this._models[i] = this._modelcls()
 			}
 		}
 		for (let i = 0; i < this._classes.length; i++) {

lib/model/ransac.js

@@ -10,7 +10,7 @@
 export default class RANSAC {
 	// https://qiita.com/kazetof/items/b3439d9258cc85ddf66b
 	/**
-	 * @param {new () => RANSACSubModel} model Function to generate the model
+	 * @param {() => RANSACSubModel} model Function to generate the model
 	 * @param {number | null} [sample] Sampling rate
 	 */
 	constructor(model, sample = null) {
@@ -43,7 +43,7 @@ export default class RANSAC {
 		const xt = idx.map(v => x[v])
 		const yt = idx.map(v => y[v])
 
-		const mdl = new this._model()
+		const mdl = this._model()
 		mdl.fit(xt, yt)
 
 		const pred = mdl.predict(x)