mental-health-logistic-regression

Mental Health Emotion Detection - Logistic Regression

This model performs multi-label emotion classification for mental health applications, detecting 28 different emotions from text input.

Model Description

• Model Type: Logistic Regression (Multi-Output Classifier)
• Framework: scikit-learn
• Task: Multi-label emotion classification
• Dataset: GoEmotions (balanced subset)
• Languages: English

Performance

Emotions Detected

The model can detect 28 emotions: admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise, neutral.

Usage

import pickle
import requests

# Using HuggingFace Inference API
API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/mental-health-logistic-regression"
headers = {"Authorization": "Bearer YOUR_HF_TOKEN"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

# Example usage
result = query({"inputs": "I'm feeling really anxious about tomorrow"})
print(result)

Training Details

• Training Data: Balanced GoEmotions dataset (~15,000 samples)
• Features: TF-IDF vectorization
• Preprocessing: Contraction expansion, lowercase normalization
• Class Balancing: Advanced sampling techniques for rare emotions

Intended Use

This model is designed for mental health applications, chatbots, and emotion-aware systems. It provides high recall for detecting emotional states that might require support or intervention.

Limitations

• Trained primarily on English text
• Performance may vary with informal language or slang
• Should not be used as sole diagnostic tool for mental health

Citation

If you use this model, please cite:

@misc{mental-health-emotion-logistic,
  title={Mental Health Emotion Detection - Logistic Regression},
  author={Your Name},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/YOUR_USERNAME/mental-health-logistic-regression}
}