tpot - A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming

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Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data.

machine-learning data-science automl automation scikit-learn hyperparameter-optimization model-selection parameter-tuning automated-machine-learning random-forest gradient-boosting feature-engineering xgboost genetic-programming

scoruby - Ruby Scoring API for PMML

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Ruby scoring API for Predictive Model Markup Language (PMML).Currently supports Decision Tree, Random Forest Naive Bayes and Gradient Boosted Models.

ruby-gem pmml random-forest classification rubyml machine-learning gradient-boosting-classifier gbm gradient-boosted-models decision-tree naive-bayes

random-forest-classifier - A random forest classifier in Javascript.

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A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting.Modeled after scikit-learn's RandomForestClassifier.

random-forest machine-learning classifier

decision-tree-js - Small JavaScript implementation of ID3 Decision tree

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Small JavaScript implementation of algorithm for training Decision Tree and Random Forest classifiers.

decision-tree random-forest machine-learning

edarf - exploratory data analysis using random forests

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Functions useful for exploratory data analysis using random forests. This package extends the functionality of random forests fit by party (multivariate, regression, and classification), randomForestSRC (regression and classification,), randomForest (regression and classification), and ranger (classification and regression).

random-forest r rstats exploratory-data-analysis machine-learning