diffuser34/autotrain-uzdtm-nwkp2

Model Trained Using AutoTrain

• Problem type: Tabular regression

Validation Metrics

• r2: 0.5287307064016351
• mse: 3.103168000915719e+19
• mae: 2243863540.8
• rmse: 5570608585.168877
• rmsle: 8.027979609819264
• loss: 5570608585.168877

Best Params

• learning_rate: 0.11299209471906922
• reg_lambda: 1.95078305416454e-06
• reg_alpha: 0.03568550183373181
• subsample: 0.6486218191662874
• colsample_bytree: 0.22654368454464396
• max_depth: 1
• early_stopping_rounds: 481
• n_estimators: 20000
• 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