ipinthearipin/monthly-expense-predictor

🧠 Monthly Expense Predictor

This is a regression model trained with scikit-learn to predict monthly expenses based on average daily costs.

🔢 Input Features

{
  "avg_food": 40000,
  "avg_transport": 20000,
  "avg_shopping": 15000,
  "avg_others": 5000,
  "days_logged": 30
}

📈 Output

{
  "predicted_monthly_expense": 2400000.00
}

🧪 Usage in Python

from huggingface_hub import hf_hub_download
from joblib import load
import numpy as np

model_path = hf_hub_download(repo_id="your-username/monthly-expense-predictor", filename="monthly_expense_predictor.joblib")
model = load(model_path)

input_data = np.array([[40000, 20000, 15000, 5000, 30]])
prediction = model.predict(input_data)
print(f"Prediction: Rp{prediction[0]:,.2f}")