---
tags:
- autotrain
- tabular
- regression
- tabular-regression
datasets:
- rea-ridge/autotrain-data
---

# Model Trained Using AutoTrain

- Problem type: Tabular regression

## Validation Metrics

- r2: 0.19049946745813506
- mse: 2090173568.9542394
- mae: 38517.69777526885
- rmse: 45718.41608098688
- rmsle: 0.22010094141328534
- loss: 45718.41608098688

## Best Params

- alpha: 0.0007335286293009105
- fit_intercept: True
- max_iter: 9736

## Usage

```python
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

```