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TF-IDF + One-vs-Rest Logistic Regression

This repository contains a classical machine learning model trained with TF-IDF features and One-vs-Rest Logistic Regression for multi-label mental health classification.

Model

Feature extraction: TF-IDF (word + char)
Classifier: One-vs-Rest Logistic Regression
Framework: scikit-learn

Files

best_sklearn_no_fasttext.joblib : trained model

Usage

import joblib
model = joblib.load('best_sklearn_no_fasttext.joblib')

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