I am working stack overflow tag predictor.
I have a dataframe df which contains a feature 'post' and label 'Tags' which can be multi lable.
My df is :
Tags post
0 [php] check upload file image without mime type woul...
1 [firefox] prevent firefox close press ctrl-w favorite ed...
2 [r] r error invalid type list variable import matl...
3 [c#] replace special character url probably simple ...
4 [php, api] modify whois contact detail function modify mc...
... ... ...
179995 [delphi] intraweb isapi module throw unrecognized comma...
179996 [c] opencv argc argv confusion check opencv tutori...
179997 [android] list data sdcard want display file name reside...
179998 [java, email] add sort extension imap server mail server sup...
179999 [linux, php] create carddav ldap server share host via php ...
So I want to use word2vec for classification and predict the tags.
I want to use all machine learning classifier like SVM, random forest etc.
I also want classification report of tags.
So please help me.
word2vec is not a classifier it word to vector converter, my suggestion steps 1) Preprocess the text(like stopwords and normalization) 2) convert the words to vector using TF-IDF or word2vec 3) Then apply ml models (for multi classification you can use SVM, Naive Bayes and logistic regression) 4)validate the results
I completed it by TF-IDF . By I don't know how to do it with word2vec..Please can give me a Code.
stackoverflow.com/questions/22129943/…..
go through the about stack you eill get idea.. you have to import using genism and use