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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StackGenVis/frontend/node_modules/gray-matter/package.json

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4.0 KiB

{
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"_where": "/Users/anchaa/Documents/Research/iStacking_code/istacking/frontend/node_modules/parser-front-matter",
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"url": "https://github.com/jonschlinkert"
},
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"bugs": {
"url": "https://github.com/jonschlinkert/gray-matter/issues"
},
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"contributors": [
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"name": "Andrew Meyer",
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},
{
"name": "Brian Woodward",
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},
{
"name": "Caesar Schinas",
"url": "https://caesarschinas.com"
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{
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{
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{
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"deprecated": false,
"description": "Parse front-matter from a string or file. Fast, reliable and easy to use. Parses YAML front matter by default, but also has support for YAML, JSON, TOML or Coffee Front-Matter, with options to set custom delimiters. Used by metalsmith, assemble, verb and many other projects.",
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"main": "index.js",
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"url": "git+https://github.com/jonschlinkert/gray-matter.git"
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"typings": "gray-matter.d.ts",
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