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

# Model Trained Using AutoTrain

- Problem type: Tabular regression

## Validation Metrics

- r2: -13.723120886842382
- mse: 38015883737.055504
- mae: 174448.73032973852
- rmse: 194976.62356563544
- rmsle: 2.6073960566969823
- loss: 194976.62356563544

## Best Params

- C: 60.27729201980406
- fit_intercept: False
- loss: epsilon_insensitive
- epsilon: 0.00020827552565594136
- max_iter: 9903

## 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

```