GitHub / mahnoorsheikh16 / NLP-Approach-to-AI-Text-Classification

A text‐classification pipeline for identifying human‐ versus AI-generated responses using engineered linguistic/semantic features and PCA-reduced vectors; achieves ~85% accuracy with Logistic Regression, SVM, and MLP, and includes a fine-tuned bert-base-uncased model.

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Topics: bert-model, countvectorizer, decision-tree-classifier, feature-engineering, gaussian-naive-bayes, gradient-boosting-classifier, hyperparameter-tuning, kfold-cross-validation, knn-classification, logistic-regression, matplotlib-pyplot, mlp-classifier, pca-analysis, plotly, random-forest-classifier, seaborn-plots, streamlit-dashboard, svm-classifier, text-classification, tokenization

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