Hi all, if you are not sure what is the deliverables of the final project, please following the guidelines below: 1. The code for data training for both TF_IDF and 3-Gram methods. 2. The code for...

for data mgnt


Hi all, if you are not sure what is the deliverables of the final project, please following the guidelines below: 1. The code for data training for both TF_IDF and 3-Gram methods. 2. The code for twitter data cleasing. 3. The code for sentiment analyzing obama and romney data. 4. final calculated positive ratios. 5. The code for saving data to MongoDB. MongoDB Class 635 Final Project Using spark and mongodb Twitter Analysis for Presidential Election Download obama.csv and romney.csv from blackboard project content Use clean_twitter.csv we learnt from last class as the training set. First repeat the code you leant from last class to train TF-IDF with logistic regression model Write a code to read obama.csv and romney.csv Clean the text in obama.csv and romney.csv, i.e. strip off unnecessary characters from data Feed data into TF-IDF with logistic regression model and calculate the ratio of positive posts vs total posts for both obama and romney. Change model to 3-gram with logistic regression model. Re-calculate the result. Store these two dataframes with their sentiments value into a MongoDB.