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        "author": "Miles Granger <miles59923@gmail.com>",
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        "description": "# pyrus-decision-tree\nDecision Tree written in Rust, with Python bindings\n\n## Extremely _slow_ Decision Tree written in Rust \n\nHave you found yourself yerning for a _slower_ version of Scikit-Learn's\n`DecisionTreeClassifier` with less features? \n\nYou've come to the right place.\n\nThis was a weekend project and I've botched the implementation somewhere,\nprobably in the splitter logic for tree nodes, so while it's written\nentirely in Rust and requires no dependencies; it manages to do a lot\nof inefficient logic, very quickly.\n\nOn a handful of testing data, with equivelent parameters, it yields \nthe same results, only much, much slower. \n\n*This is currently the first release and the tree only implements \nthe `scikit-learn` API's `fit(X, y)` and `predict(X)` methods as of now, \nand only as a classifier (no regression tree yet)*\n\n\nMaybe I'll get back to fixing it, maybe not. \n\n\n---\n\n#### Install:\n`pip install --upgrade pyrus-decision-tree`\n\n#### Uninstall:\n`pip uninstall pyrus-decision-tree`\n\n---\n\n#### Use:\n```python\nfrom pyrus_decision_tree import PyrusDecisionTree\n\ndataset = [[2.771244718, 1.7847839292],\n           [1.728571309, 1.1697614132],\n           [3.678319846, 2.812813571],\n           [3.961043357, 2.619950321],\n           [2.999208922, 2.209014212],\n           [7.497545867, 3.162953546],\n           [9.00220326,  3.339047188],\n           [7.444542326, 0.476683375],\n           [10.12493903, 3.234550982],\n           [6.642287351, 3.319983761]]\ntargets = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1]\n\nclf = PyrusDecisionTree(5)\nclf.fit(dataset, targets)\npredictions = clf.predict(dataset)\n```\n",
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