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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50 lines
1.1 KiB
50 lines
1.1 KiB
'use strict'
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var tape = require('tape')
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var shuffle = require('shuffle-array')
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var compareCells = require('../compare')
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function testStability(t, array) {
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var expected = array.slice().sort(compareCells).map(function(c) {
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return c.slice().sort()
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}).join(':')
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for(var i=0; i<10; ++i) {
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var actual = shuffle(array).sort(compareCells).map(function(c) {
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return c.slice().sort()
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}).join(':')
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t.equals(actual, expected)
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}
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}
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tape('stability test - homog dimension', function(t) {
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for(var d=1; d<=5; ++d) {
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for(var n=0; n<10; ++n) {
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var cells = new Array(100)
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for(var j=0; j<100; ++j) {
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var c = cells[j] = new Array(d)
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for(var k=0; k<d; ++k) {
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c[k] = (Math.random() * 20)|0
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}
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}
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testStability(t, cells)
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}
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}
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t.end()
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})
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tape('stability test - mixed dimension', function(t) {
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for(var n=0; n<10; ++n) {
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var cells = []
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for(var d=1; d<=5; ++d) {
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for(var j=0; j<10; ++j) {
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var c = new Array(d)
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for(var k=0; k<d; ++k) {
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c[k] = (Math.random() * 20)|0
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}
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cells.push(c)
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}
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}
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testStability(t, cells)
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}
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t.end()
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})
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