SparkBOOST is a Java library built over Apache Spark that provides a distributed implementation of AdaBoost.MH and MP-Boost machine learning algorithms. These boosting algorithms are known to be very effective and robust to overfitting in many application domains, e.g. in natural language processing contexts. SparkBOOST offers to developers a fast way to scale these algorithms to large scale problems, where one needs to build classifiers from very large training datasets or simply needs to quickly classify huge stream of documents. The library can be integrated into custom programs by using a simple API. The SparkBOOST implementation also provides some command line tools to perform learning and classification on data sources available in LibSVM format.
SparkBOOST
Fagni T
2016
Abstract
SparkBOOST is a Java library built over Apache Spark that provides a distributed implementation of AdaBoost.MH and MP-Boost machine learning algorithms. These boosting algorithms are known to be very effective and robust to overfitting in many application domains, e.g. in natural language processing contexts. SparkBOOST offers to developers a fast way to scale these algorithms to large scale problems, where one needs to build classifiers from very large training datasets or simply needs to quickly classify huge stream of documents. The library can be integrated into custom programs by using a simple API. The SparkBOOST implementation also provides some command line tools to perform learning and classification on data sources available in LibSVM format.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
