Let's take a look at the various components of Mahout.
The following table represents the high-level design of a Mahout implementation. Machine learning applications access the API, which provides support for implementing different machine learning techniques, such as clustering, classification, and recommendations.
Also, if the application requires preprocessing (for example, stop word removal and stemming) for text input, it can be achieved with Apache Lucene. Apache Hadoop provides data processing and storage to enable scalable processing.
Also, there will be performance optimizations using Java Collections and the Mahout-Math library. The Mahout-integration library contains utilities such as displaying ...