We need your help! 🔥
Please consider disabling your ad-blocker to support this website! 🔑
We are a free, community-supported website! 🥰
We only display small unobtrusive ads which help us stay online! 💯
Thank you in advance! ❤️
We are a free, community-supported website! 🥰
We only display small unobtrusive ads which help us stay online! 💯
Thank you in advance! ❤️
Light Gbm Multiclass Classifier
The LightGBM trainer is an open source implementation of gradient boosting decision tree.
Inputs
| Name | ID | Description | Type |
|---|---|---|---|
| Evaluation Metric | Eval Metric | Determines which evaluation metric to use:\n 1) Default\n 2) Error\n 3) Log Loss\n 4) None | Integer |
| Learning Rate | Learning Rate | The shrinkage rate for trees, used to prevent over-fitting. Valid range is [0,1]. | Number |
| Sigmoid Parameter | Sigmoid | Determines the steepness of the sigmoid function | Number |
| Use SoftMax | Use Softmax | Determines whether to use the SoftMax loss function. The SoftMax function is a generalization of the logistic function to multiple dimensions. | Boolean |
| Max Bins Per Feature | Max Bins | The maximum number of bins that feature values will be bucketed in. A small number of bins may reduce training accuracy but may increase general power (deal with over-fitting). | Integer |
Outputs
| Name | ID | Description | Type |
|---|---|---|---|
| Trainer Type | Trainer Type | The trainer used for machine learning problems. | Generic |
Site design © Robin Rodricks.
LunchBox and associated data © 2024 Nathan Miller.
Rhinoceros and Grasshopper are registered trademarks of Robert McNeel & Associates.
Hosted by GitHub