atheno3/autotrain-700h1-dxj41

Model Trained Using AutoTrain

• Problem type: Tabular classification

Validation Metrics

• auc: 1.0
• logloss: 0.02560930807260143
• f1: 1.0
• accuracy: 1.0
• precision: 1.0
• recall: 1.0
• loss: 0.02560930807260143

Best Params

• learning_rate: 0.22611071522667908
• reg_lambda: 0.03493387873764126
• reg_alpha: 2.9837721474835582e-05
• subsample: 0.912493466832241
• colsample_bytree: 0.50276453147468
• max_depth: 1
• early_stopping_rounds: 144
• n_estimators: 20000
• eval_metric: logloss

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