Mahout
Mahout is the Apache library for open source learning. Mahout mainly uses, but is not limited to, the classification and dimensional algorithms of clustering recommend engines (collaborative filtering and classification). Mahout's objective is to provide the usual machine learning algorithms with a highly scalable implementation. If the historical data to be used is large, then Mahout is the machinery of choice. We generally find that it is not possible to process the data on a single device. With large data becoming an important area of focus, Mahout meets the need for a machine learning tool that can extend beyond a single computer. Mahout is different from other tools such as R, Weka, and so on, as its emphasis on scalability. The Mahout learning implementations are written in Java, and most but not all of them are compiled using the MapReduce paradigm on Apache's distributed Hadoop calculation project. Mahout will be built using Scala DSL on Apache Spark, and programs written...
