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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59 lines
1.3 KiB
59 lines
1.3 KiB
4 years ago
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const regl = require('regl')({ extensions: 'oes_element_index_uint' })
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const createMatrix = require('../')
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let splom = createMatrix(regl)
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splom.update({
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data: [
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[0, 1, 2, 3, 4, 5, 10],
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[0, 1, 2, 3, 4, 5, 10],
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[0, 1, 2, 3, 4, 5, 10]
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],
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ranges: [
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[0, 10],
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[0, 10],
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[0, 10]
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],
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domain: [
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[0, 0, 0.333, 0.333],
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[0.3333, 0.3333, 0.66666, 0.66666],
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[0.66666, 0.66666, 1, 1]
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],
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// domain: [
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// [0, 0, 0.5, null],
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// [0.5, 0, 1, 0.5],
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// [null, 0.5, 1, 1]
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// ],
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adjustDomain: true,
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diagonal: false,
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lower: false
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})
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splom.draw()
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splom.destroy()
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// adjust domain when only half is visible
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// if (!trace.diagonal && (!trace.upper || !trace.lower) && trace.adjust) {
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// let shift = 1 / trace.domain.length
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// if (trace.upper) {
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// trace.domain.forEach((d, i) => {
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// d[1] = (d[1] - shift) / (1 - shift)
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// d[3] = (d[3] - shift) / (1 - shift)
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// d[0] = (d[0]) / (1 - shift)
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// d[2] = (d[2]) / (1 - shift)
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// })
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// }
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// else if (trace.lower) {
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// trace.domain.forEach((d, i) => {
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// d[1] = (d[1]) / (1 - shift)
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// d[3] = (d[3]) / (1 - shift)
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// d[0] = (d[0] - shift) / (1 - shift)
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// d[2] = (d[2] - shift) / (1 - shift)
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// })
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// }
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// }
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