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Sdca Maximum Entropy Multiclass Classifier
The Sdca maximum entropy model is used to predict a target using a linear multiclass classifier model trained with a coordinate descent method.
Inputs
| Name | ID | Description | Type |
|---|---|---|---|
| Convergence Tolerance | Convergence | The tolerance for the ratio between duality gap and primal loss for convergence checking. | Number |
| Bias Learning Rate | Bias | The learning rate for adjusting bias from being regularized. | Number |
| L1 Regularization | L1 Regularization | The L1 regularization weight. | Number |
| L2 Regularization | L2 Regularization | The L2 regularization weight. | Number |
| Shuffle | Shuffle | Determines whether to shuffle data for each training iteration. | Boolean |
Outputs
| Name | ID | Description | Type |
|---|---|---|---|
| Trainer Type | Trainer Type | The trainer used for machine learning problems. | Generic |
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