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.
A Machine Learning package for Q2 Strategies implementing various generic algorithms
Formats and cleans your data to get it ready for machine learning!
Train machine learning models in pure Javascript using battle-tested implementations that improve on Python's sklearn and R's caret.
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 j
logistic regression/c4.5 decision tree algorithm with random forest
the author don't update the npm , so i forked one;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 an
Decision Tree Based Methodology Revisited and Revived.