coan/botClaiton

Model Trained Using AutoTrain

• Problem type: Tabular regression

Validation Metrics

• r2: 0.9984848248937886
• mse: 2414.5671496869554
• mae: 25.17867390839041
• rmse: 49.13824528498098
• rmsle: 0.026803719250247764
• loss: 49.13824528498098

Best Params

• learning_rate: 0.021447034999088264
• reg_lambda: 1.8519959907940258e-07
• reg_alpha: 0.4126490352165311
• subsample: 0.2980305940030723
• colsample_bytree: 0.9624113264792772
• max_depth: 6
• early_stopping_rounds: 213
• 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