🎉Community Raffle - Win $25

An exclusive raffle opportunity for active members like you! Complete your profile, answer questions and get your first accepted badge to enter the raffle.
Join and Win

TF-IDF and Aspect grouping with Rapid Miner

User: "HeikoeWin786"
New Altair Community Member
Updated by Jocelyn
Dear all,
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,
Hikoe

Find more posts tagged with