DP1110/mlp-accessibility-model

title: MLP Accessibility Score Predictor emoji: 🚀 colorFrom: red colorTo: pink sdk: fastapi appfile: app.py requirementsfile: requirements.txt ---

MLP Accessibility Score Predictor

This Hugging Face Space hosts a FastAPI application that uses a pre-trained Multi-layer Perceptron (MLP) Regressor to predict urban accessibility scores. The model and its associated imputer are loaded directly from the Hugging Face Hub.

How to use:

Send a POST request to the /predict endpoint with a JSON body containing the input features for which you want to predict the accessibility score. The expected features are based on the training data and include indicators such as % ASF (Euclidean), % Built-Up Area, etc.

Example Request Body (JSON):

{
  "perc_ASF_Euclidean": 0.6,
  "perc_Built_up_Area": 0.7,
  "perc_ASF_Network": 0.55,
  "perc_ASFS_from_Buffer_Distance_of_BS": 0.65,
  "Overall_Accessibility_Score": 0.62
}

(Note: The 'OverallAccessibilityScore' is the target, but for prediction, you would typically provide values for the features and the model predicts the score. The app.py expects individual feature values.)

Access the API endpoint at https://[your-space-name].hf.space/predict.