POS Tagging using SVM

This Python program implements a Part-of-Speech (POS) tagging system using Support Vector Machines (SVM). POS tagging is a fundamental task in Natural Language Processing (NLP) where each word in a sentence is assigned a corresponding grammatical category such as noun, verb, adjective, etc.

Overview

The program follows these main steps:

1. Data Loading: Loads the training and testing data from text files.
2. Feature Extraction: Extracts relevant features from the input data.
3. Data Preprocessing: Splits the data into training and testing sets, vectorizes features, and scales them.
4. Training and Evaluation: Trains an SVM classifier using the training data and evaluates its performance on the testing data.