farrukhshahzad25/autotrain-vessel-eta

Model Trained Using AutoTrain

• Problem type: Tabular regression

Validation Metrics

• r2: 0.2033836841583252
• mse: 53092.500978994
• mae: 150.96381290340423
• rmse: 230.41810037189788
• rmsle: 0.9569819523414094
• loss: 230.41810037189788

Best Params

• learning_rate: 0.0695392185390836
• reg_lambda: 0.00017542491817558795
• reg_alpha: 0.6577124531542021
• subsample: 0.3632574815242663
• colsample_bytree: 0.8007491192913739
• max_depth: 4
• early_stopping_rounds: 166
• 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