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---
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
```
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