Master 4.24.0

src/class/learning/Classification.js

@@ -1,8 +1,6 @@
 import InputPopup from './InputPopup';
 
-export const classes = [
-    'ai_learning_speech'
-];
+export const classes = ['ai_learning_speech'];
 
 class Classification {
     #type = null;
@@ -20,9 +18,11 @@ class Classification {
 
     getResult(index) {
         const result = this.#popup?.result || [];
-        const defaultResult = {probability: 0, className: ''};
-        if(index !== undefined && index > -1) {
-            return result.find(({className}) => className === this.#labels[index]) || defaultResult;
+        const defaultResult = { probability: 0, className: '' };
+        if (index !== undefined && index > -1) {
+            return (
+                result.find(({ className }) => className === this.#labels[index]) || defaultResult
+            );
         }
         return result[0] || defaultResult;
     }
@@ -36,10 +36,10 @@ class Classification {
 
     openInputPopup() {
         this.#popup = new InputPopup({
-            url: this.#url, 
+            url: this.#url,
             labels: this.#labels,
             type: this.#type,
-            recordTime: this.#recordTime
+            recordTime: this.#recordTime,
         });
         this.#popup.open();
     }

src/class/learning/Cluster.js

@@ -1,6 +1,7 @@
 import { kmpp } from 'skmeans/kinit';
 // import { kmpp } from 'skmeans/dist/node/kinit';
 import floor from 'lodash/floor';
+import _toNumber from 'lodash/toNumber';
 import LearningView from './LearningView';
 import Chart from './Chart';
 import DataTable from '../DataTable';
@@ -153,14 +154,17 @@ class Cluster {
         this.#trainCallback(1);
         this.#isTrained = false;
         const { data, select } = this.#table;
+        const filtered = data.filter(
+            (row) => !select.flat().some((selected) => !_toNumber(row[selected]))
+        );
         const [attr] = select;
 
         const { centroids, indexes } = kmeans(
-            data.map((row) => attr.map((i) => parseFloat(row[i]) || 0)),
+            filtered.map((row) => attr.map((i) => parseFloat(row[i]) || 0)),
             this.#trainParam
         );
         this.#result = {
-            graphData: convertGraphData(data, centroids, indexes, attr),
+            graphData: convertGraphData(filtered, centroids, indexes, attr),
             centroids,
         };
         this.#isTrained = true;

src/class/learning/DecisionTree.js

@@ -3,6 +3,7 @@ import _floor from 'lodash/floor';
 import _max from 'lodash/max';
 import _sum from 'lodash/sum';
 import _mean from 'lodash/mean';
+import _toNumber from 'lodash/toNumber';
 import LearningBase from './LearningBase';
 import { DecisionTreeClassifier as DTClassifier } from 'ml-cart';
 import Utils from './Utils';
@@ -24,7 +25,7 @@ class DecisionTree extends LearningBase {
     type = 'decisiontree';
 
     init({ name, url, result, table, trainParam }) {
-        this.name = name; 
+        this.name = name;
         this.trainParam = trainParam;
         this.result = result;
         this.table = table;
@@ -157,8 +158,10 @@ function getData(testRate = 0.2, data) {
     const tempMapCount = {};
     const { select = [[0], [1]], data: table, fields } = data;
     const [attr, predict] = select;
-
-    const dataArray = table
+    const filtered = table.filter(
+        (row) => !select.flat().some((selected) => !_toNumber(row[selected]))
+    );
+    const dataArray = filtered
         .map((row) => ({
             x: attr.map((i) => Utils.stringToNumber(i, row[i], tempMap, tempMapCount)),
             y: Utils.stringToNumber(predict[0], row[predict[0]], tempMap, tempMapCount),
@@ -176,7 +179,7 @@ function getData(testRate = 0.2, data) {
         select,
         fields,
         valueMap: { ...tempMap[predict[0]] },
-        numClass: tempMapCount[predict[0]],
+        numClass: tempMapCount[predict[0]] || 1,
     };
 }
 

src/class/learning/LogisticRegression.js

@@ -3,6 +3,7 @@ import _floor from 'lodash/floor';
 import _max from 'lodash/max';
 import _sum from 'lodash/sum';
 import _mean from 'lodash/mean';
+import _toNumber from 'lodash/toNumber';
 import LearningBase from './LearningBase';
 import Utils from './Utils';
 
@@ -182,8 +183,10 @@ function getData(validationRate, testRate, data, trainParam) {
     const tempMapCount = {};
     const { select = [[0], [1]], data: table, fields } = data;
     const [attr, predict] = select;
-
-    const dataArray = table
+    const filtered = table.filter(
+        (row) => !select.flat().some((selected) => !_toNumber(row[selected]))
+    );
+    const dataArray = filtered
         .map((row) => ({
             x: attr.map((i) => Utils.stringToNumber(i, row[i], tempMap, tempMapCount)),
             y: Utils.stringToNumber(predict[0], row[predict[0]], tempMap, tempMapCount),