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HaajraMumtaz/
LahoreTrafficPredictor

Name: LahoreTrafficPredictor
Availability: InStock

apache-2.0

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Essential metadata for Hugging Face

license: apache-2.0 tags:

tabular-regression
traffic-prediction
catboost
lahore datasets:
HaajraMumtaz/LahoreTrafficData metrics:
mae
rmse

Lahore Route Predictor 🚦

This model predicts the congestion_multiplier for various routes in Lahore, Pakistan. It uses a CatBoost regressor trained on historical traffic patterns to estimate how much slower a trip will be compared to free-flow traffic given coordinates, type of day and time of day etc

How to Use

To load and use this model, you need the catboost library installed.

Loading the Model

python

from catboost import CatBoostRegressor

model = CatBoostRegressor()
model.load_model("model.cbm") # Ensure this file is in your folder

Making a Prediction

The model expects features in the following order: origin_zone, dest_zone, road_type, speed_limit_kmh, num_lanes, is_one_way, distance_km, road_curvature, has_signal, is_construction, weather_condition, day_of_week, time_slot, is_weekend, is_holiday, day_type.

Training & Evaluation

Algorithm: CatBoost Regressor
Data Source: https://huggingface.co/datasets/HaajraMumtaz/LahoreTrafficData
Key Features: Road type, construction status, and weather (especially Smog/Rain).

HaajraMumtaz/LahoreTrafficPredictor