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This article introduces the relevant knowledge of "the method of installation and deployment of Mahout-0.9". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

1. Go to the official to download the latest version

2. Configure environment variables

Export MAHOUT_HOME=/home/wukong/usr/mahout-0.9/export MAHOUT_CONF_DIR=/home/wukong/usr/mahout-0.9/confexport PATH=$PATH:$MAHOUT_HOME/conf:$MAHOUT_HOME/bin

3. Start the test

[wukong@bd23 ~] $mahoutMAHOUT_LOCAL is not set Adding HADOOP_CONF_DIR to classpath.Running on hadoop Using / home/wukong/usr/hadoop-2.4.1/bin/hadoop and HADOOP_CONF_DIR=/home/wukong/usr/hadoop-2.4.1/etc/hadoop/MAHOUT-JOB: / home/wukong/usr/mahout-0.9/mahout-examples-0.9-job.jarAn example program must be given as the first argument.Valid program names are: arff.vector:: Generate Vectors from an ARFF file or directory baumwelch:: Baum-Welch algorithm for unsupervised HMM training canopy:: Canopy Clustering cat:: Print a file or resource as the logistic regression models would see it cleansvd:: Cleanup and verification of SVD output clusterdump:: Dump cluster output to text clusterpp:: Groups Clustering Output In Clusters cmdump:: Dump confusion matrix in HTML or text formats concatmatrices:: Concatenates 2 matrices of same cardinality into a single matrix cvb:: LDA via Collapsed Variation Bayes (0th deriv. Approx) cvb0_local:: LDA via Collapsed Variation Bayes, in memory locally. EvaluateFactorization:: compute RMSE and MAE of a rating matrix factorization against probes fkmeans:: Fuzzy K-means clustering hmmpredict:: Generate random sequence of observations by given HMM itemsimilarity:: Compute the item-item-similarities for item-based collaborative filtering kmeans:: K-means clustering lucene.vector:: Generate Vectors from a Lucene index lucene2seq:: Generate Text SequenceFiles from a Lucene index matrixdump:: Dump matrix in CSV format matrixmult:: Take the product of two matrices parallelALS:: ALS-WR factorization of a rating matrix qualcluster:: Runs Clustering experiments and summarizes results in a CSV recommendfactorized:: Compute recommendations using the factorization of a rating matrix recommenditembased:: Compute recommendations using item-based collaborative filtering regexconverter:: Convert text files on a per line basis based on regular expressions resplit:: Splits a set of SequenceFiles into a number of equal splits rowid:: Map SequenceFile to {SequenceFile SequenceFile} rowsimilarity:: Compute the pairwise similarities of the rows of a matrix runAdaptiveLogistic:: Score new production data using a probably trained and validated AdaptivelogisticRegression model runlogistic:: Run a logistic regression model against CSV data seq2encoded:: Encoded Sparse Vector generation from Text sequence files seq2sparse:: Sparse Vector generation from Text sequence files seqdirectory:: Generate sequence files (of Text) from a directory seqdumper:: Generic SequenceFile dumper seqmailarchives:: Creates SequenceFile from a directory containing gzipped mailarchives seqwiki:: Wikipedia xml dump to sequence file spectralkmeans:: Spectral k- Means clustering split:: Split Input data into test and train sets splitDataset:: split a rating dataset into training and probe parts ssvd:: Stochastic SVD streamingkmeans:: Streaming k-means clustering svd:: Lanczos Singular Value Decomposition testnb:: Test the Vector-based Bayes classifier trainAdaptiveLogistic:: Train an AdaptivelogisticRegression model trainlogistic:: Train a logistic regression using stochastic gradient descent trainnb:: Train the Vector-based Bayes classifier transpose:: Take the transpose of a matrix validateAdaptiveLogistic:: Validate an AdaptivelogisticRegression model against hold-out dataset vecdist:: Compute the distances between a set of Vectors (or Cluster or Canopy They must fit in memory) and a list of Vectors vectordump:: Dump vectors from a sequence file to text viterbi:: Viterbi decoding of hidden states from given output states sequence "method of installation and deployment of Mahout-0.9" ends here Thank you for your reading. If you want to know more about the industry, you can follow the website, the editor will output more high-quality practical articles for you!

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