XGBoostSageMakerEstimator¶
Type¶
ml-estimator
Class¶
fire.nodes.sagemaker.NodeXGBoostSageMakerEstimator
Fields¶
| Name | Title | Description |
|---|---|---|
| roleArn | Role Arn | Role arn to use sagemaker |
| trainingInstanceType | Training Instance Type | InstanceType for training |
| trainingInstanceCount | Training Instance Count | Number of Instance for training |
| endpointInstanceType | Endpoint Instance Type | InstanceType for Endpoint |
| endpointInitialInstanceCount | Endpoint Initial Instance Count | Number of Instance for Endpoint |
| booster | Booster | Select the type of model to run at each iteration. It has 2 options: gbtree: tree-based models & gblinear: linear models |
| silent | Silent | Silent mode is activated is set to 1, i.e. no running messages will be printed |
| nthread | NThread | If you wish to run on all cores, value should not be entered and algorithm will detect automatically |
| objective | Objective | This defines the loss function to be minimized |
| numTrees | Num Trees | The number of rounds for boosting |
| numClasses | Num Classes | For Objective: multi:softmax, you also need to set an additional num_class (number of classes) parameter defining the number of unique classes |
| seed | Seed | Can be used for generating reproducible results and also for parameter tuning |