nicoler229/p2

Model Trained Using AutoTrain

• Problem type: Tabular regression

Validation Metrics

• r2: 0.8987710422047952
• mse: 15.386801584871137
• mae: 3.1008129119873047
• rmse: 3.9226013798079378
• rmsle: 0.049014949862444
• loss: 3.9226013798079378

Best Params

• learning_rate: 0.09858308825036341
• reg_lambda: 1.7244892825164977e-06
• reg_alpha: 0.004880162297132929
• subsample: 0.5918267532876357
• colsample_bytree: 0.6228647593929555
• max_depth: 8
• early_stopping_rounds: 440
• n_estimators: 7000
• 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