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analyzing data that is labeled with positive ( +1) and negative (-1),
Dear Guys ,,
how are you? many thanks for your help ,, i really need your advice ,, firstly , I have analyse my data that is labeled with positive ( +1) and negative (-1), " what i do is I put every single comment in a text file and create 2 folders the first is for positive comments and the other is for negative comments ,then I analyze them i use KNN and SVM "
Now i have build a lexicon as a CSV file , every word and its weight , i need to enhance my results by using the lexicon weights , so how you can help me to use weights of the new lexicon with the weights that I have from the SVM model ??
what i have to do ?
many thanks in advance , i appreciated your help
0
Answers
Do you want to add the weights from SVM as new features? If so, you can join the weight table with the vectorized text. The weights from SVM is usually used to explain the feature importance, select features for dimension reduction, and normalize input data by feature weights. Take a look at the tutorial process of "select by weights" and "scale by weights" operator.
Cheers,
YY
i think to use the update model to update my results and to use the words in lexicon that is matches in the data file that i use before ,, what is ur advice ??
i will attach my work ,, but the update model tells me there is an error some where ,, i need some help pleease !!!
any help or any informations ??