Sentiment Classification using N-gram IDF and Automated Machine Learning To buy this project in ONLINE, Contact: Email: jpinfotechprojects@gmail.com, Website: https://www.jpinfotech.org

1. Sentiment Classification using N-gram IDF and Automated
Machine Learning
ABSTRACT:
We propose a sentiment classification method with a general machine learning
framework. For feature representation, n-gram IDF is used to extract software-
engineering related, dataset-specific, positive, neutral, and negative n-gram
expressions. For classifiers, an automated machine learning tool is used. In the
comparison using publicly available datasets, our method achieved the highest F1
values in positive and negative sentences on all datasets.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System : Pentium Dual Core.
 Hard Disk : 120 GB.
 Monitor : 15’’ LED
 Input Devices : Keyboard, Mouse
 Ram : 1 GB
SOFTWARE REQUIREMENTS:
 Operating system : Windows 7.
 Coding Language : Python
 Database : MYSQL

2. REFERENCE:
Rungroj Maipradit_, Hideki Hata_, Kenichi Matsumoto, “Sentiment Classification
using N-gram IDF and Automated Machine Learning”, IEEE Software, 2019