Model Trained Using AutoTrain
- Problem type: Tabular regression
Validation Metrics
- r2: 0.9988073651686958
- mse: 337854.8880689932
- mae: 398.9371570016889
- rmse: 581.2528606974706
- rmsle: 0.01184006241771929
- loss: 581.2528606974706
Best Params
- learning_rate: 0.09168110099890295
- reg_lambda: 0.11592417839619104
- reg_alpha: 0.0010410090431649107
- subsample: 0.357364833100802
- colsample_bytree: 0.9155936367985213
- max_depth: 7
- early_stopping_rounds: 158
- 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)