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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 = 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
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