And can also you check that in target folder contains  .class file
generated or not .

Syed Abdul kather
send from Samsung S3
On Jul 28, 2012 8:32 PM, "syed kather" <[email protected]> wrote:

>
> Hi ,
>   The way you have installed mahout may be wrong .. can I know whether out
> of box in mahout is working fine .
> Syed Abdul kather
> send from Samsung S3
> On Jul 28, 2012 5:35 AM, "k6.amruta [via Lucene]" <
> [email protected]> wrote:
>
>> I am trying to run Wikipedia Bayes Example from
>> https://cwiki.apache.org/confluence/...+Bayes+Example
>>
>> When I ran the following command : $MAHOUT_HOME/bin/mahout
>> wikipediaXMLSplitter -d
>> $MAHOUT_HOME/examples/temp/enwiki-latest-pages-articles10.xml -o
>> wikipedia/chunks -c 64
>>
>> I am getting this error:
>>
>> Exception in thread "main" java.lang.NoClassDefFoundError: classpath
>> Caused by: java.lang.ClassNotFoundException: classpath
>>         at java.net.URLClassLoader$1.run(URLClassLoader.java:217)
>>         at java.security.AccessController.doPrivileged(Native Method)
>>         at java.net.URLClassLoader.findClass(URLClassLoader.java:205)
>>         at java.lang.ClassLoader.loadClass(ClassLoader.java:323)
>>         at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:294)
>>         at java.lang.ClassLoader.loadClass(ClassLoader.java:268)
>>         at java.lang.ClassLoader.loadClassInternal(ClassLoader.java:336)
>> Running on hadoop, using /x/home/hadoop_adm/opt/hadoop/bin/hadoop and
>> HADOOP_CONF_DIR=
>> MAHOUT-JOB:
>> /x/home/user/mahout-distribution-0.7/mahout-examples-0.7-job.jar
>> 12/07/27 16:28:02 WARN driver.MahoutDriver: Unable to add class:
>> wikipediaXMLSplitter
>> 12/07/27 16:28:02 WARN driver.MahoutDriver: No wikipediaXMLSplitter.props
>> found on classpath, will use command-line arguments only
>> Unknown program 'wikipediaXMLSplitter' chosen.
>> 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
>>   cvb: : LDA via Collapsed Variation Bayes (0th deriv. approx)
>>   cvb0_local: : LDA via Collapsed Variation Bayes, in memory locally.
>>   dirichlet: : Dirichlet Clustering
>>   eigencuts: : Eigencuts spectral clustering
>>   evaluateFactorization: : compute RMSE and MAE of a rating matrix
>> factorization against probes
>>   fkmeans: : Fuzzy K-means clustering
>>   fpg: : Frequent Pattern Growth
>>   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
>>   matrixdump: : Dump matrix in CSV format
>>   matrixmult: : Take the product of two matrices
>>   meanshift: : Mean Shift clustering
>>   minhash: : Run Minhash clustering
>>   parallelALS: : ALS-WR factorization of a rating matrix
>>   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
>>   rowid: : Map SequenceFile<Text,VectorWritable> to
>> {SequenceFile<IntWritable,VectorWritable>, SequenceFile<IntWritable,Text>}
>>   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 Sequence File dumper
>>   seqmailarchives: : Creates SequenceFile from a directory containing
>> gzipped mail archives
>>   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
>>   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 data set
>>   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
>>
>>
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>




-----
THANKS AND REGARDS,
SYED ABDUL KATHER
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