# LightGBM Example

This example trains a LightGBM classifier with the iris dataset and logs hyperparameters, metrics, and trained model.

## Running the code

```
python train.py --colsample-bytree 0.8 --subsample 0.9
```

You can try experimenting with different parameter values like:

```
python train.py --learning-rate 0.4 --colsample-bytree 0.7 --subsample 0.8
```

Then you can open the MLflow UI to track the experiments and compare your runs via:

```
mlflow server
```

## Running the code as a project

```
mlflow run . -P learning_rate=0.2 -P colsample_bytree=0.8 -P subsample=0.9
```