Accord.NET-SVM Repo

Project Description

Machine Learning Application that performs Sentiment Classification(Fine-Grained, emotions) with sparse text representations(TFIDF) or pre-trained dense word vectors(Word2Vec), on Supervised Linear Model(SVM). The Classification result is later dumped in local storage as a Confusion Matrix(CM) Analysis. The implementation of the project was based on Accord.NET, a Machine Learning Framework written completely in Csharp for production-grade application development.

App.Config

• Basic Configurations of IO operations
• Text Representations(TFIDF-W2V)
• SVM model setup

Forms of Text Representations

• TFIDF - Sparse
• Word2Vec(W2V) - Dense

Forms of Linear Optimization Function/Solver

• SMO(Sequential Minimization Optimization)
• LCD(Linear Coordinate Descent)

Prerequisite:Accord.NET