Email-Sentiment-Analysis

This repository consits of analysizing the sentiment of an email, classifying it as negative or positive and predicting the happiness quotient of the week on the basis of the training data. The email data set consits of emails extracted from my gmail account. You can also download your mailbox from https://takeout.google.com/settings/takeout here and convert the .mbox to .eml files The presentation (http://prezi.com/s-ggob34somq/?utm_campaign=share&utm_medium=copy) explains the conceptual flow of the system. Three algorithms were tested; Linear Model,Naive Bayes and Random Forest. The confidence can very of each model with the data. The model which was best suited for my model was Random Forest and hence I used it for further predictions. The happiness quotient is calculated on the basis of how many emails are negative or positive of the past week.