I am new to Weka.
I am trying to run some algorithms in Weka using UCI ML repository but I don't know how to use the .names and .data files in Weka.
Can anyone tell me how to convert .data and .name to arff format?
Please look at the "creating a .arff file" section in http://storm.cis.fordham.edu/~gweiss/data-mining/weka.html
If you want a simpler solution using only the .data file (.names are related to data description): just edit the .data file, insert a header (insert a first line with a different name for each attribute and all separated by a comma), save and rename it to .csv. Be careful that this solution shall not handle properly non basic data types and encounter problems with missing values.
I'm not sure if this helps but other way to use your data is to create an .arff like the example:
http://www.let.rug.nl/~coltekin/ml08/weather.arff
if your database are simple you can just make your own .arff if you wanna use a bigger database using .csv then transform into arff is more recommended
Related
I'm trying to extract data from the PennTreeBank, Wall Street Journal corpus. Most of it already has the parse trees, but some of the data is only tagged.
i.e. wsj_DDXX.mrg and wsj_DDXX.pos files.
I would like to use the already parsed trees and tagged data in these files so as not to use the parser and taggers within CoreNLP, but I still want the output file format that CoreNLP gives; namely, the XML file that contains the dependencies, entity coreference, and the parse tree and tagged data.
I've read many of the java docs but I cannot figure out how to get it the way I described.
For POS, I tried using the LexicalizedParser and it allows me to use the tags, but I can only generate an XML file with the some of the information I want; there is no option for coreference or generating the parse trees. To get it to correctly generate the sub-optimal XML files here, I had to write a script to get rid of all of the brackets within the files. This is the command I use:
java -cp "*" edu.stanford.nlp.parser.lexparser.LexicalizedParser -outputFormat typedDependenciesCollapsed,wordsAndTags -outputFilesExtension xml -outputFormatOptions xml -writeOutputFiles -outputFilesDirectory my\dir -tokenized -tagSeparator / -tokenizerFactory edu.stanford.nlp.process.WhitespaceTokenizer -tokenizerMethod newCoreLabelTokenizerFactory edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz my\wsj\files\dir
I also can't generate the data I would like to have for the WSJ data that already has the trees. I tried using what is said here and I looked at the corresponding Javadocs. I used the command similar to what is described. But I had to write a python program to retrieve the stdout data resulting from analyzing each file and wrote it into a new file. This resulting data is only a text file with the dependencies and is not in the desired XML notation.
To summarize, I would like to use the POS and tree data from these PTB files in order to generate a CoreNLP parse corresponding to what would occur if I used CoreNLP on a regular text file. The pseudo command would be like this:
java -cp "*" edu.stanford.nlp.pipeline.CoreNLP -useTreeFile wsj_DDXX.mrg
and
java -cp "*" edu.stanford.nlp.pipeline.CoreNLP -usePOSFile wsj_DDXX.pos
Edit: fixed a link.
Yes, this is possible, but a bit tricky and there is no out of the box feature that can do this, so you will have to write some code. The basic idea is to replace the tokenize, ssplit and pos annotators (and in case you also have trees the parse annotator) with your code that loads these annotations from your annotated files.
On a very high level you have to do the following:
Load your trees with MemoryTreebank
Loop through all the trees and for each tree create a sentence CoreMap to which you add
a TokensAnnotation
a TreeAnnotation and the SemanticGraphCoreAnnotations
Create an Annotation object with a list containing the CoreMap objects for all sentences
Run the StanfordCoreNLP pipeline with the annotators option set to lemma,ner,dcoref and the option enforceRequirements set to false.
Take a look at the individual annotators to see how to add the required annotations. E.g. there is a method in ParserAnnotatorUtils that adds the SemanticGraphCoreAnnotations.
I'm using C SPSS I/O library to write and read sav files.
I need to store my own version number in sav file. The requirements are:
1) That version should not be visible to user when he/she uses regular SPSS programs.
2) Obviously, regular SPSS programs and the I/O module should not overwrite the number.
Please, advice about that place or function.
Regards,
There is a header field in the sav file that identifies the creator. However, that would be overwritten if the file is resaved. It would be visible with commands such as sysfile info.
Another approach would be to create a custom file attribute using a name that is unlikely to be used by anyone else. It would also be visible in a few system status commands such as DISPLAY DICT and I think, CODEBOOK. It could be overwritten, with the DATASET ATTRIBUTE command but would not be changed just by resaving the file.
I am trying to use OpenNLP in a project I am working in and i am very new to it. I tried out using the Named Entity Recognition with the training data available at http://opennlp.sourceforge.net/models-1.5/
However I want to see the training data that have been used. i.e. to actually open the .bin file and see its content in English. Can some one pls point me in the correct direction.
I have tried to use UltraISO to read the .bin file but i was not successful.
PLs help !!
Thanx :)
Use the Unix file command to find the file type, like file en-token.bin. For most OpenNLP .bin files, it will tell you that these are just ZIP files.
the bin file is actually the bytes of a serialized java object representing a TokenNameFinder implementation called a NameFinderME (ME meaning Maximum entropy, which is the main multinomial logistic regression (ish) algorithm used in OpenNLP). You will not be able to see the training data by doing anything to this file.
Correction: it's not the name finder, it's the namefinderMODEL that is serialized.
I know how to convert a Set of text or web page files in to arff file using TextDirectoryLoader.
I want to know how to convert a single Text file in to Arff file.
Any help will be highly appreciated.
Please be more specific. Anyway:
If the text in the file corresponds to a single document (that it, a
single instance), then all you need is to replace all "new lines"
with the escape code \n to make the full text be in a single line,
then manually format as an arff with a single text attribute and a
single instance.
If the text corresponds to several instances (e.g. documents), then I
suggest to make an script to break it into several files and to apply
TextDirectoryLoader. If there is any specific formating (e.g.
instances are enclosed in XML tags), you can either do the same (by
taking advantage of the XML format), or to write a custom Loader
class in WEKA to recognize your format and build an Instances object.
If you post an example, it would be easier to get a more precise suggestion.
I just started learning how to use mahout. I'm not a java programmer however, so I'm trying to stay away from having to use the java library.
I noticed there is a shell tool regexconverter. However, the documentation is sparse and non instructive. Exactly what does specifying a regex option do, and what does the transformer class and formatter class do? The mahout wiki is marvelously opaque. I'm assuming the regex option specifies what counts as a "unit" or so.
The example they list is of using the regexconverter to convert http log requests to sequence files I believe. I have a csv file with slightly altered http log requests that I'm hoping to convert to sequence files. Do I simply change the regex expression to take each entire row? I'm trying to run a Bayes classifier, similar to the 20 newsgroups example which seems to be done completely in the shell without need for java coding.
Incidentally, the arff.vector command seems to allow me to convert an arff file directly to vectors. I'm unfamiliar with arff, thought it seems to be something I can easily convert csv log files into. Should I use this method instead, and skip the sequence file step completely?
Thanks for the help.