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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31 lines
1.0 KiB
31 lines
1.0 KiB
4 years ago
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var test = require("tap").test;
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var closestPoint1d = require("../lib/closest_point_1d.js");
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var closestPointnd = require("../lib/closest_point_nd.js");
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test("1d closest point", function(t) {
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for(var d=2; d<6; ++d) {
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var p0 = new Array(d);
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var p1 = new Array(d);
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var x = new Array(d);
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var r0 = new Array(d);
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var r1 = new Array(d);
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for(var n=0; n<100; ++n) {
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for(var i=0; i<d; ++i) {
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p0[i] = Math.random() * 10.0 - 5.0;
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p1[i] = Math.random() * 10.0 - 5.0;
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x[i] = Math.random() * 10.0 - 5.0;
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}
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var d0 = closestPoint1d(p0, p1, x, r0);
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var d1 = closestPointnd([0,1], [p0, p1], x, r1);
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if(isNaN(d1)) {
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console.warn("closest_point_nd failed: ", p0, p1, x, d0, r0);
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continue;
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}
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t.assert(Math.abs(d0 - d1) < 1e-4, "check d:" + d0 + " ~ " + d1 + "; p0:"+p0 + ", p1:" + p1 + ", x:" + x);
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for(var i=0; i<d; ++i) {
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t.assert(Math.abs(r0[i] - r1[i]) < 1e-4, "check r:" + r0 + " ~ " + r1);
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}
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}
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}
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t.end();
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});
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