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download][download-image]][download-url]\n\nDecision trees using CART implementation.\n\n## Installation\n\n`npm i ml-cart`\n\n## [API documentation](http://mljs.github.io/decision-tree-cart/)\n\n## Usage\n\n### As a classifier\n\n```js\nimport irisDataset from 'ml-dataset-iris';\nimport { DecisionTreeClassifier as DTClassifier } from 'ml-cart';\n\nconst trainingSet = irisDataset.getNumbers();\nconst predictions = irisDataset\n  .getClasses()\n  .map((elem) => irisDataset.getDistinctClasses().indexOf(elem));\n\nconst options = {\n  gainFunction: 'gini',\n  maxDepth: 10,\n  minNumSamples: 3,\n};\n\nconst classifier = new DTClassifier(options);\nclassifier.train(trainingSet, predictions);\nconst result = classifier.predict(trainingSet);\n```\n\n### As a regression\n\n```js\nimport { DecisionTreeRegression as DTRegression } from 'ml-cart';\n\nconst x = new Array(100);\nconst y = new Array(100);\nconst val = 0.0;\nfor (let i = 0; i < x.length; ++i) {\n  x[i] = val;\n  y[i] = Math.sin(x[i]);\n  val += 0.01;\n}\n\nconst reg = new DTRegression();\nreg.train(x, y);\nconst estimations = reg.predict(x);\n```\n\n## License\n\n[MIT](./LICENSE)\n\n[npm-image]: https://img.shields.io/npm/v/ml-cart.svg\n[npm-url]: https://npmjs.org/package/ml-cart\n[ci-image]: https://github.com/mljs/decision-tree-cart/workflows/Node.js%20CI/badge.svg?branch=master\n[ci-url]: https://github.com/mljs/decision-tree-cart/actions?query=workflow%3A%22Node.js+CI%22\n[download-image]: https://img.shields.io/npm/dm/ml-cart.svg\n[download-url]: 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