Support Vector Machine (SVM) Estimator

About:

The SVM Classifier Dashboard is a comprehensive, interactive web application built with Streamlit that makes Support Vector Machine (SVM) classification accessible to everyone - from beginners learning machine learning to experienced data scientists who need quick model prototyping.

🎯 Purpose & Value Proposition

What Problem Does It Solve?

Complex ML Made Simple: Traditional SVM implementation requires extensive coding knowledge.

Parameter Confusion: Understanding SVM hyperparameters can be overwhelming.

Model Management: Difficult to save, load, and reuse trained models.

Production Gap: Moving from experimentation to real predictions is complex.

Technical Specification:

Data Transformation Steps

CSV Parsing: pd.read_csv() with error handling

One-hot Detection: Automatic binary encoding detection

Label Encoding: Categorical target conversion

Feature Scaling: MinMaxScaler normalization

Data Splitting: Stratified train/validation/test splits