Work

Text recognition and Sentiment Analysis

Neural Network
Training
Dataset
View on GitHub

We used some pre-existing code from Prof. Asa Ben-Hur to compare sentiment analysis accuracy between LSTM, SVM, logistic regression, and random forest classification models.

Random Forest Classifier that was used for sentiment analysis.

'CS345-Text-Recognition' is a repository dedicated to exploring and comparing the accuracy of various machine learning models in the field of sentiment analysis. The models we focus on include LSTM (Long Short-Term Memory), SVM (Support Vector Machines), logistic regression, and random forest classification models. The code in this repository is built upon pre-existing code from Prof. Asa Ben-Hur. This project serves as a comprehensive study of different approaches to text recognition and sentiment analysis, providing valuable insights into the strengths and weaknesses of each model.