SMU Data Science Review
Most Popular Papers *
Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets
Kaitlin Kirasich, Trace Smith, and Bivin Sadler
Cryptocurrency Price Prediction Using Tweet Volumes and Sentiment Analysis
Jethin Abraham, Daniel Higdon, John Nelson, and Juan Ibarra
Fake News Detection: A Deep Learning Approach
Aswini Thota, Priyanka Tilak, Simrat Ahluwalia, and Nibrat Lohia
Multi-Modal Classification Using Images and Text
Stuart J. Miller, Justin Howard, Paul Adams, Mel Schwan, and Robert Slater
Supervised Machine Learning Bot Detection Techniques to Identify Social Twitter Bots
Phillip George Efthimion, Scott Payne, and Nicholas Proferes
Improve Image Classification Using Data Augmentation and Neural Networks
Shanqing Gu, Manisha Pednekar, and Robert Slater
Phishing Detection Using Natural Language Processing and Machine Learning
Apurv Mittal, Dr Daniel Engels, Harsha Kommanapalli, Ravi Sivaraman, and Taifur Chowdhury
Toxic Comment Classification
Sara Zaheri, Jeff Leath, and David Stroud
Identification and Classification of Poultry Eggs: A Case Study Utilizing Computer Vision and Machine Learning
Jeremy Lubich, Kyle Thomas, and Daniel W. Engels
Employee Attrition: What Makes an Employee Quit?
Alex Frye, Christopher Boomhower, Michael Smith, Lindsay Vitovsky, and Stacey Fabricant
* Based on the average number of full-text downloads per day since the paper was posted.
» Updated as of 01/08/24.
