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[80, 60, 10, 20, 30];\nlet outputs = [20, 40, 30, 50, 60];\n\nlet regression = new SLR(inputs, outputs);\nregression.toString(3) === \"f(x) = - 0.265 * x + 50.6\";\n```\n\n#### External links\n\nCheck this cool blog post for a detailed example:\nhttps://hackernoon.com/machine-learning-with-javascript-part-1-9b97f3ed4fe5\n\n### Polynomial regression\n\n```js\nconst PolynomialRegression = require(\"ml-regression\").PolynomialRegression;\nconst x = [50, 50, 50, 70, 70, 70, 80, 80, 80, 90, 90, 90, 100, 100, 100];\nconst y = [\n  3.3, 2.8, 2.9, 2.3, 2.6, 2.1, 2.5, 2.9, 2.4, 3.0, 3.1, 2.8, 3.3, 3.5, 3.0,\n];\nconst degree = 5; // setup the maximum degree of the polynomial\nconst regression = new PolynomialRegression(x, y, degree);\nconsole.log(regression.predict(80)); // Apply the model to some x value. 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