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TF-IDF and Aspect grouping with Rapid Miner
I am new to RapidMiner and I got few questions really seeking your kind support.
I have a airline dataset with labelled data of sentiment (pos, neg, and netural).
I had divided the dataset 75/25 data split and perform the text processing (i.e. nominal to text, data to document, preprocess document with tokenization, stopwords).
Q1: However, when the result out in word from preprocess document operator, I found the neg,pos and netural data columns have all zero value. Is this normal or am I missing something?
Q2: I want to perform the aspect categorization i.e. I have 5 topics as aspect groups (e.g. flight, service, ...) and the output of TF-IDF consists of the highest frequency words, and those words I want to group under the 5 topics. After that, I will perform Navies Bayes Classification to know the sentiment classification for each aspects. Is there any efficient way I can perform this in RapidMiner?
I am a really starter in Rapidminer and i am so sorry if I am asking very basic questions. But, I do hope your kind support in helping me to learn this.
Thanks and regarda,