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XGBoost is a library from [DMLC](http://dmlc.ml/). It is designed and optimized for boosted trees. The underlying algorithm of XGBoost is an extension of the classic gbm algorithm. With multi-threads and regularization, XGBoost is able to utilize more computational power and get a more accurate prediction.\n\nThe package is made to run existing XGBoost model with Node.js easily.\n\n### Features\n\n+ Runs XGBoost Model and make predictions in Node.js.\n\n+ Both dense and sparse matrix input are supported, and missing value is handled.\n\n+ Supports Linux, macOS.\n\n### Install\n\nInstall from npm\n\n```bash\nnpm install xgboost\n```\n\nInstall from GitHub\n\n```bash\ngit clone --recursive git@github.com:nuanio/xgboost-node.git\nnpm install\n```\n\n### Documentation\n\n+ [Introduction to XGBoost-Node](./doc/intro.md)\n\n+ [APIs Documentation](./doc/api.md)\n\n+ [Unit Tests Cases](./test/base.js)\n\n+ [中文简介](./doc/intro_zh.md)\n\n### Roadmap\n\n+ [x] Matrix API\n+ [x] Model API\n+ [x] Prediction API\n+ [x] Async API\n+ [ ] Windows Support\n+ [ ] Training API\n+ [ ] Visualization API\n\n### Examples\n\nTrain a XGBoost model and save to a file, more in [doc](./doc/intro.md#user-content-usage).\n\nLoad the model with XGBoost-Node:\n\n```javascript\nconst xgboost = require('xgboost');\nconst model = xgboost.XGModel('iris.xg.model');\n\nconst input = new Float32Array([\n  5.1,  3.5,  1.4,  0.2, // class 0\n  6.6,  3. ,  4.4,  1.4, // class 1\n  5.9,  3. ,  5.1,  1.8  // class 2\n]);\n\nconst mat = new xgboost.matrix(input, 3, 4);\nconsole.log(model.predict(mat));\n// {\n//   value: [\n//     0.991, 0.005, 0.004, // class 0\n//     0.004, 0.990, 0.006, // class 1\n//     0.005, 0.035, 0.960, // class 2\n//   ],\n//   error: undefined,      // no error\n// }\n\nconst errModel = xgboost.XGModel('data/empty');\nconsole.log(errModel);\nconsole.log(errModel.predict());\n```\n\n# Contributing\n\nYour help and contribution is very valuable. Welcome to submit issue and pull requests. [Learn more](./.github/CONTRIBUTING.md)\n","readmeFilename":"readme.md"}