StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
https://doi.org/10.1109/TVCG.2020.3030352
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41 lines
1.2 KiB
41 lines
1.2 KiB
import { Bar } from '../BaseCharts';
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import { reactiveData } from '../mixins';
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export default {
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extends: Bar,
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mixins: [reactiveData],
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data: function data() {
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return {
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chartData: '',
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options: {
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responsive: true,
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maintainAspectRatio: false
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}
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};
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},
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created: function created() {
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this.fillData();
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},
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mounted: function mounted() {
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var _this = this;
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this.renderChart(this.chartData, this.options);
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setInterval(function () {
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_this.fillData();
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}, 5000);
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},
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methods: {
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fillData: function fillData() {
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this.chartData = {
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labels: ['January' + this.getRandomInt(), 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'],
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datasets: [{
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label: 'Data One',
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backgroundColor: '#f87979',
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data: [this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt(), this.getRandomInt()]
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}]
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};
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},
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getRandomInt: function getRandomInt() {
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return Math.floor(Math.random() * (50 - 5 + 1)) + 5;
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}
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}
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}; |