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 | |
``` | |