#Utils
org.apache.mahout.utils.vectors.VectorDumper = vectordump : Dump vectors from a sequence file to text
org.apache.mahout.utils.clustering.ClusterDumper = clusterdump : Dump cluster output to text
org.apache.mahout.utils.SequenceFileDumper = seqdumper : Generic Sequence File dumper
org.apache.mahout.utils.vectors.lucene.Driver = lucene.vector : Generate Vectors from a Lucene index
org.apache.mahout.utils.vectors.arff.Driver = arff.vector : Generate Vectors from an ARFF file or directory
org.apache.mahout.utils.vectors.RowIdJob = rowid : Map SequenceFile<Text,VectorWritable> to {SequenceFile<IntWritable,VectorWritable>, SequenceFile<IntWritable,Text>}
org.apache.mahout.utils.SplitInput = split : Split Input data into test and train sets
org.apache.mahout.utils.MatrixDumper = matrixdump : Dump matrix in CSV format
org.apache.mahout.utils.regex.RegexConverterDriver = regexconverter : Convert text files on a per line basis based on regular expressions
org.apache.mahout.text.SequenceFilesFromDirectory = seqdirectory : Generate sequence files (of Text) from a directory
org.apache.mahout.vectorizer.SparseVectorsFromSequenceFiles = seq2sparse: Sparse Vector generation from Text sequence files
org.apache.mahout.vectorizer.EncodedVectorsFromSequenceFiles = seq2encoded: Encoded Sparse Vector generation from Text sequence files
org.apache.mahout.text.WikipediaToSequenceFile = seqwiki : Wikipedia xml dump to sequence file
org.apache.mahout.text.SequenceFilesFromMailArchives = seqmailarchives : Creates SequenceFile from a directory containing gzipped mail archives
org.apache.mahout.text.SequenceFilesFromLuceneStorageDriver = lucene2seq : Generate Text SequenceFiles from a Lucene index
org.apache.mahout.utils.ConcatenateVectorsJob = concatmatrices : Concatenates 2 matrices of same cardinality into a single matrix
org.apache.mahout.clustering.streaming.tools.ResplitSequenceFiles = resplit : Splits a set of SequenceFiles into a number of equal splits
org.apache.mahout.clustering.streaming.tools.ClusterQualitySummarizer = qualcluster : Runs clustering experiments and summarizes results in a CSV
org.apache.mahout.classifier.df.tools.Describe = describe : Describe the fields and target variable in a data set

#Math
org.apache.mahout.math.hadoop.TransposeJob = transpose : Take the transpose of a matrix
org.apache.mahout.math.hadoop.MatrixMultiplicationJob = matrixmult : Take the product of two matrices
org.apache.mahout.math.hadoop.decomposer.DistributedLanczosSolver = svd : Lanczos Singular Value Decomposition
org.apache.mahout.math.hadoop.decomposer.EigenVerificationJob = cleansvd : Cleanup and verification of SVD output
org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob = rowsimilarity : Compute the pairwise similarities of the rows of a matrix
org.apache.mahout.math.hadoop.similarity.VectorDistanceSimilarityJob =  vecdist : Compute the distances between a set of Vectors (or Cluster or Canopy, they must fit in memory) and a list of Vectors
org.apache.mahout.math.hadoop.stochasticsvd.SSVDCli = ssvd : Stochastic SVD

#Clustering
org.apache.mahout.clustering.kmeans.KMeansDriver = kmeans : K-means clustering
org.apache.mahout.clustering.fuzzykmeans.FuzzyKMeansDriver = fkmeans : Fuzzy K-means clustering
org.apache.mahout.clustering.lda.cvb.CVB0Driver = cvb : LDA via Collapsed Variation Bayes (0th deriv. approx)
org.apache.mahout.clustering.lda.cvb.InMemoryCollapsedVariationalBayes0 = cvb0_local : LDA via Collapsed Variation Bayes, in memory locally.
org.apache.mahout.clustering.canopy.CanopyDriver = canopy : Canopy clustering
org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver = spectralkmeans : Spectral k-means clustering
org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver = clusterpp : Groups Clustering Output In Clusters
org.apache.mahout.clustering.streaming.mapreduce.StreamingKMeansDriver = streamingkmeans : Streaming k-means clustering

#Classification
#new bayes
org.apache.mahout.classifier.naivebayes.training.TrainNaiveBayesJob = trainnb : Train the Vector-based Bayes classifier
org.apache.mahout.classifier.naivebayes.test.TestNaiveBayesDriver = testnb : Test the Vector-based Bayes classifier
org.apache.mahout.classifier.df.mapreduce.BuildForest = buildforest : Build the random forest classifier
org.apache.mahout.classifier.df.mapreduce.TestForest = testforest : Test the random forest classifier

#SGD
org.apache.mahout.classifier.sgd.TrainLogistic = trainlogistic : Train a logistic regression using stochastic gradient descent
org.apache.mahout.classifier.sgd.RunLogistic = runlogistic : Run a logistic regression model against CSV data
org.apache.mahout.classifier.sgd.PrintResourceOrFile = cat : Print a file or resource as the logistic regression models would see it
org.apache.mahout.classifier.sgd.TrainAdaptiveLogistic = trainAdaptiveLogistic : Train an AdaptivelogisticRegression model
org.apache.mahout.classifier.sgd.ValidateAdaptiveLogistic = validateAdaptiveLogistic : Validate an AdaptivelogisticRegression model against hold-out data set
org.apache.mahout.classifier.sgd.RunAdaptiveLogistic = runAdaptiveLogistic : Score new production data using a probably trained and validated AdaptivelogisticRegression model
#HMM
org.apache.mahout.classifier.sequencelearning.hmm.BaumWelchTrainer = baumwelch : Baum-Welch algorithm for unsupervised HMM training
org.apache.mahout.classifier.sequencelearning.hmm.ViterbiEvaluator = viterbi : Viterbi decoding of hidden states from given output states sequence
org.apache.mahout.classifier.sequencelearning.hmm.RandomSequenceGenerator = hmmpredict : Generate random sequence of observations by given HMM
#Classifier Utils
org.apache.mahout.classifier.ConfusionMatrixDumper = cmdump : Dump confusion matrix in HTML or text formats

#Recommenders
org.apache.mahout.cf.taste.hadoop.als.DatasetSplitter = splitDataset : split a rating dataset into training and probe parts
org.apache.mahout.cf.taste.hadoop.als.FactorizationEvaluator = evaluateFactorization : compute RMSE and MAE of a rating matrix factorization against probes
org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob = itemsimilarity : Compute the item-item-similarities for item-based collaborative filtering
org.apache.mahout.cf.taste.hadoop.item.RecommenderJob = recommenditembased : Compute recommendations using item-based collaborative filtering
org.apache.mahout.cf.taste.hadoop.als.ParallelALSFactorizationJob = parallelALS : ALS-WR factorization of a rating matrix
org.apache.mahout.cf.taste.hadoop.als.RecommenderJob = recommendfactorized : Compute recommendations using the factorization of a rating matrix
prepare20newsgroups = deprecated : Try the new vector backed naivebayes classifier see examples/bin/classify-20newsgroups.sh 
trainclassifier = deprecated : Try the new vector backed naivebayes classifier see examples/bin/classify-20newsgroups.sh 
testclassifier = deprecated : Try the new vector backed naivebayes classifier see examples/bin/classify-20newsgroups.sh 
lda = deprecated : Try the new Collapsed Variation Bayes LDA, try bin/mahout cvb or bin/mahout cvb0_local
ldatopics = deprecated : Try the new Collapsed Variation Bayes LDA, try bin/mahout cvb or bin/mahout cvb0_local