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package.json

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{
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"name": "ppComplete",
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"version": "0.5.0",
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"description": "automated machine learning! push button ensembling, grid search for javascript neural network",
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"name": "machinejs",
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"version": "0.7.0",
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"description": "Automated machine learning structure. Ensembles random forests, XGBoost, neural networks, AdaBoost, KNN, SVM together, handling data formatting ensembling, and running predictions for you. Feel free to tweak the settings if you want a lot of control, or just start it up and let it run if you're looking for a push-button MVP solution.",
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"main": "ppLib.js",
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"scripts": {
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"test": "echo \"Error: no test specified\" && exit 1"
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},
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"repository": {
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"type": "git",
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"url": "http://github.com/ClimbsRocks/ppComplete.git"
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"url": "http://github.com/ClimbsRocks/machinejs.git"
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},
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"keywords": [
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"neuralNet",
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"machine",
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"learning",
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"neural network",
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"machine learning",
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"ml",
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"algorithms",
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"random",
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"forest",
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"random forest",
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"svm",
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"naive",
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"bayes",
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"naive bayes",
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"bagging",
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"optimization",
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"data",
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"science",
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"data science",
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"brainjs",
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"neural",
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"networks",
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"date",
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"night"
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"date night",
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"scikit-learn",
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"sklearn",
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"ensemble",
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"data formatting",
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"javascript",
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"js",
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"XGBoost",
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"scikit-neuralnetwork",
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"KNN",
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"K nearest neighbors",
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"GridSearch",
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"GridSearchCV",
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"grid search",
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"python",
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"RandomizedSearchCV",
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"preprocessing",
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"data-formatter",
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"SVM",
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"kaggle",
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"kaggle competition"
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],
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"author": "Preston Parry",
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"license": "MIT",
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"bugs": {
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"url": "https://github.com/ClimbsRocks/ppComplete/issues"
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"url": "https://github.com/ClimbsRocks/machineJS/issues"
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},
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"homepage": "https://github.com/ClimbsRocks/ppComplete",
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"homepage": "https://github.com/ClimbsRocks/machineJS",
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"dependencies": {
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"brain": "^0.7.0",
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"data-formatter": "^1.3.0",

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