3 packages on CRAN
2 packages on GitHub
Data Warehouse, Business Intelligence, data integration helpers. Unifies database connectors to DBI, RJDBC, RODBC, csv. Easy managing multiple simultaneous db connections. MDX like queries on cube class object. Data modelling helpers, denormalization of star schema and snowflake schema, basic normalization. And more.
Utilities related to Bitcoin. Unified markets API interface (bitstamp, kraken, btce, bitmarket). Both public and private API calls. Integration of data structures for all markets. Support SSL. Read Rbitcoin documentation (command: ?btc) for more information.
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML).
Automates and ensures high quality output for most of your machine learning and data science tasks. The package contains high quality functions that run at efficient speed with minimal memory constraints for supervised learning, unsupervised learning, feature engineering, model evaluation and interpretation, along with some helper functions for graphing. AutoCatBoostClassifier(), AutoCatBoostRegression(), and AutoCatBoostMultiClass() have a dependency to the catboost package which isn't part of the CRAN repository at the time of this writing. The link to the catboost URL to download the package for use is in the Additional_repositories field below, which has the installation instructions. You need to install that package to make use of the AutoCatBoost_ functions.