NodeJS Implementation of Decision Tree using ID3 Algorithm.
When building the decision tree you must provide both the training data and the feature names. Do not provide a name for your label column as it is assumed that the last column in the training data represents the labels.
A utility for traversing decision trees by selecting options
NodeJS implementation of decision tree, random forest, and XGBoost algorithms with comprehensive performance testing (Node.js 20+)
A simple class to make statefull decision trees
Get the unscoped, camelCased name of a npm package
Web component - Wizard
Array#isArray for older browsers
CLI arguments parser. Native port of python's argparse.
Get the command from a shebang
Callback wrapping utility
JSON parse & stringify that supports binary via bops & base64
Resolve the path of a module like `require.resolve()` but from a given path
Run a function exactly one time
Allows users to use generators in order to write common functions that can be both sync or async.
ECMAScript AST recursive visitor
deterministic `JSON.stringify()` - a faster version of substack's json-stable-strigify without jsonify
process.nextTick but always with args
deterministic JSON.stringify() with custom sorting to get deterministic hashes from stringified results, with no public domain dependencies
Light ECMAScript (JavaScript) Value Notation - human written, concise, typed, flexible
Fast (and loose) selective `process.env` replacer using js-tokens instead of an AST
Pass two numbers, get a regex-compatible source string for matching ranges. Validated against more than 2.78 million test assertions.
Use node's fs.realpath, but fall back to the JS implementation if the native one fails
Buffers events from a stream until you are ready to handle them.