# Model description
This is a Logistic Regression model trained on iris dataset. This model could beused to predict type of iris flower, given certain dimensions. This model is very basic andshould only be used as an example of how to use Highwind.
## Intended uses & limitations
This model is made for the purposes of showing how to use Highwind only.
## Training Procedure
[More Information Needed]
### Hyperparameters
Click to expand
| Hyperparameter | Value |
|-------------------|---------|
| C | 1 |
| class_weight | |
| dual | False |
| fit_intercept | True |
| intercept_scaling | 1 |
| l1_ratio | |
| max_iter | 100 |
| multi_class | auto |
| n_jobs | |
| penalty | l2 |
| random_state | 42 |
| solver | lbfgs |
| tol | 0.0001 |
| verbose | 0 |
| warm_start | False |
LogisticRegression(C=1, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
LogisticRegression(C=1, random_state=42)