Refer to Collections and Stream Hosts to understand more about Collections.
The following list contains definitions of all parameters, but the combination of parameters used by each algorithm differs.
Last updated
| Property | Description |
|---|---|
| Property | Description |
|---|---|
| Property | Description |
|---|---|
| Property | Description |
|---|---|
| Name | Description |
|---|---|
Collection
This associates the Agent to a specific Collection (default to that of the current Data Stream).
Learning Algorithm
The algorithm used to train the model.
Dataset
The dataset file used to train the algorithm.
Has Header
Tick to auto-populate the feature names from the first row of the training file, or the features are named column0, column1, etc.
Separator Character
The character used to separate data values in the training file.
Features (Name, Type, and Variable Type)
The grid of features is categorized by name, data type, and variable type.
Name: Feature name
Type: Data type of the feature
Variable Type: options are feature (default), exclude (ignore certain features from training), or class variable (the output).
History Size
The number of previous iterations to remember for prediction.
L1 Regularization
L1 penalty equal to the absolute value of the magnitude of coefficients.
L2 Regularization
L2 penalty which is equal to the square of the magnitude of coefficients.
Learning Rate
The amount of change in model in each iteration for better prediction.
Number of Interations
The number of times algorithms parameters are updated in a single run.
Number of Trees
The total number of trees generated on training data.
Number of Leaves
The number of leaves per tree in the model.
Minimum Example Count Per Leaf
The minimum number of samples required to be at a leaf node.
Cross-Validation Folds
Indicates the number of time fitting procedure is executed on training data
Deterministic Seed
Set this to a whole number for repeatable/deterministic results across multiple trainings
Input
This endpoint is used to receive data from the parent Agent
Output
Events received by the parent Agent and predicted values are made available to this endpoint.
