Model Trained Using AutoTrain
- Problem type: Tabular regression
Validation Metrics
- r2: 0.9753017864826334
- mse: 0.3290419495851166
- mae: 0.47130432128906286
- rmse: 0.5736217826975512
- rmsle: 0.057378419858521094
- loss: 0.5736217826975512
Best Params
- learning_rate: 0.022993157585548683
- reg_lambda: 0.0030417803769039035
- reg_alpha: 0.17755049688249555
- subsample: 0.33171622212758833
- colsample_bytree: 0.10545502763287017
- max_depth: 8
- early_stopping_rounds: 387
- n_estimators: 15000
- eval_metric: rmse
Usage
import json
import joblib
import pandas as pd
model = joblib.load('model.joblib')
config = json.load(open('config.json'))
features = config['features']
data = data[features]
predictions = model.predict(data)