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indian-flight-price-advisor
ranjeet447/indian-flight-price-advisor
indian-flight-price-advisor is a machine learning model from ranjeet447. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Trained on 300,153 Indian domestic flight records covering top metro routes (DEL, BOM, BLR, CCU, HYD, MAA) to predict fair market fares in INR (₹) and deliver real-time booking advisory.
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Public
Updated Aug 26, 2026
Repo size
2.8 MB
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.joblib2.8 MB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- Aug 26, 2026
- Updated
- Aug 26, 2026
- SHA
- 6cceed3b
Datasets
Model card
From the Hugging Face model README
✈️ Indian Domestic Flight Price & 'Buy vs. Wait' Advisor Model
Trained on 300,153 Indian domestic flight records covering top metro routes (DEL, BOM, BLR, CCU, HYD, MAA) to predict fair market fares in INR (₹) and deliver real-time booking advisory.
📊 Model Performance
- Algorithm: LightGBM Regressor (Gradient Boosted Decision Trees)
- $R^2$ Score:
0.9827(98.3% variance explained) - MAPE:
12.89% - MAE:
₹2,717.21 - RMSE:
₹4,933.84
💻 How to Use in Python
from huggingface_hub import hf_hub_download
import joblib
import pandas as pd
# 1. Download Model from Hugging Face Hub
model_path = hf_hub_download(repo_id="ranjeet447/indian-flight-price-advisor", filename="model.joblib")
model = joblib.load(model_path)
# 2. Download Feast Route Stats
features_path = hf_hub_download(repo_id="ranjeet447/indian-flight-price-advisor", filename="route_features.parquet")
route_stats = pd.read_parquet(features_path)
print("✅ Model and Feast features loaded successfully!")
- License
- mit
- Languages
- en
- Created
- Aug 26, 2026
- Updated
- Aug 26, 2026