Notaspy1234/Autotrain3-0

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 = pd.read_csv("data.csv")
data = data[features]

predictions = model.predict(data)  # or model.predict_proba(data)

# predictions can be converted to original labels using label_encoders.pkl