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---
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
```
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