This project is a JavaScript utility library that simplifies cross-validation for supervised machine learning classifiers, supporting methods like k-fold and leave-p-out. It's designed for developers and data scientists working with classification models in Node.js, allowing them to evaluate model performance by generating a confusion matrix and metrics. The
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Support the dependencies of mljs/cross-validation
Generate all possible unordered samples of size m, without replacement, from a set of n objects
Confusion matrix for supervised classification
This plugin transforms ES2015 modules to CommonJS
Shared ESLint config for cheminfo and ml.js projects
Import with sanity.
ESLint rules for Jest
ESLint rule for .only blocks in mocha tests
Runs prettier as an eslint rule
Delightful JavaScript Testing.
Next-generation ES module bundler
Extend jest to assert arrays with approximate values
Iris flower data set
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