Tabular Classification
Scikit-learn
Joblib
Portuguese
GradientBoostingClassifier
graph-theory
urban-mobility
public-transport
scikit-learn
sao-paulo
brazil
Instructions to use cintia-shinoda/sp-transit-node-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use cintia-shinoda/sp-transit-node-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("cintia-shinoda/sp-transit-node-classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "GradientBoostingClassifier", | |
| "framework": "scikit-learn", | |
| "features": [ | |
| "degree", | |
| "degree_centrality", | |
| "closeness_centrality", | |
| "lat", | |
| "lon" | |
| ], | |
| "label_map": { | |
| "0": "Peripheral", | |
| "1": "Intermediate", | |
| "2": "Hub" | |
| }, | |
| "metrics": { | |
| "f1_macro_test": 0.59, | |
| "accuracy_test": 0.68, | |
| "f1_macro_cv": 0.426 | |
| }, | |
| "training": { | |
| "n_estimators": 200, | |
| "max_depth": 5, | |
| "min_samples_leaf": 10, | |
| "class_balancing": "sample_weight_balanced", | |
| "test_size": 0.2 | |
| }, | |
| "feature_importance": { | |
| "lat": 0.2793, | |
| "lon": 0.2604, | |
| "closeness_centrality": 0.2566, | |
| "degree": 0.1061, | |
| "degree_centrality": 0.0976 | |
| } | |
| } |