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Model Trained Using AutoTrain

  • Problem type: Tabular regression

Validation Metrics

  • r2: 0.004852553257630565
  • mse: 1.704782407585897
  • mae: 1.0301575550030646
  • rmse: 1.3056731626199174
  • rmsle: 0.1919556417083651
  • loss: 1.3056731626199174

Best Params

  • learning_rate: 0.16113054215755473
  • reg_lambda: 3.3566663737449463e-06
  • reg_alpha: 1.999845686956423e-05
  • subsample: 0.3521158025399591
  • colsample_bytree: 0.1661721364825762
  • max_depth: 2
  • early_stopping_rounds: 172
  • n_estimators: 20000
  • 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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