coan/autotrain-dn6m8-0r8r6

Model Trained Using AutoTrain

• Problem type: Tabular regression

Validation Metrics

• r2: 0.9984788500175956
• mse: 2424.0886496905105
• mae: 26.34647989435065
• rmse: 49.23503477901189
• rmsle: 0.028818836691457343
• loss: 49.23503477901189

Best Params

• learning_rate: 0.12077471502182306
• reg_lambda: 1.105329890230882e-08
• reg_alpha: 1.4774392499746047
• subsample: 0.73978922085205
• colsample_bytree: 0.8233279668396214
• max_depth: 4
• early_stopping_rounds: 243
• 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