Apache Mahout 0.9 发布，此版本解决了 113 个独立 JAR包 问题；包括了一些新特性， bug 修复，还删除了在 0.8 版本弃用的算法。主要更新内容如下： - MAHOUT-1245: A new and improved Mahout website based on Apache CMS - MAHOUT-1265: MultiLayer Perceptron (MLP) classifier This is an early implementation of MLP to solicit user feedback, needs to be integrated into Mahout's processing pipeline to work with Mahout's vectors. - MAHOUT-1297: Scala DSL Bindings for Mahout Math Linear Algebra. See http://weatheringthrutechdays.blogspot.com/2013/07/scala-dsl-for-mahout-in-core-linear.html - MAHOUT-1288: Recommenders as a Search. See https://github.com/pferrel/solr-recommender - MAHOUT-1300: Suport for easy functional Matrix views and derivatives - MAHOUT-1343: JSON output format for ClusterDumper - MAHOUT-1345: Enable randomised testing for all Mahout modules using Carrot RandomizedRunner. - MAHOUT-1361: Online Algorithm for computing accurate Quantiles using 1-dimensional Clustering. See https://github.com/tdunning/t-digest/blob/master/docs/theory/t-digest-paper/histo.pdffor the details. - MAHOUT-1364: Upgrade Mahout to Lucene 4.6.1 - Removed Deprecated algorithms as they have been either replaced by better performing algorithms or lacked user support and maintenance. - the usual bug fixes. 删除的算法如下： - From Clustering: Switched LDA implementation from using Gibbs Sampling to Collapsed Variational Bayes (CVB) Meanshift MinHash - removed due to poor performance, lack of support and lack of usage - From Classification (both are sequential implementations) Winnow - lack of actual usage and support Perceptron - lack of actual usage and support - Collaborative Filtering SlopeOne implementations in org.apache.mahout.cf.taste.hadoop.slopeone and org.apache.mahout.cf.taste.impl.recommender.slopeone Distributed pseudo recommender in org.apache.mahout.cf.taste.hadoop.pseudo TreeClusteringRecommender in org.apache.mahout.cf.taste.impl.recommender - Mahout Math Hadoop entropy stuff in org.apache.mahout.math.stats.entropy Apache Mahout 是 Apache Software Foundation (ASF) 开发的一个全新的开源项目，其主要目标是创建一些可伸缩的机器学习算法，供开发人员在 Apache 在许可下免费使用。该项目已经发展到了它的最二个年头，目前只有一个公共发行版。Mahout 包含许多实现，包括集群、分类、CP 和进化程序。此外，通过使用 Apache Hadoop 库，Mahout 可以有效地扩展到云中。 Mahout 项目是由 Apache Lucene（开 源搜索）社区中对机器学习感兴趣的一些成员发起的，他们希望建立一个可靠、文档翔实、可伸缩的项目，在其中实现一些常见的用于集群和分类 的机器学习算法。该社区最初基于 Ngetal. 的文章 “Map-Reduce for Machine Learning on Multicore”，但此后在发展中又并入了更多广泛的机器学习方法。 Mahout 的目标还包括：
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