| Class | Description |
|---|---|
| AUC | |
| AUCData | |
| ConfusionMatrix | |
| CreateFrame |
Create a Frame from scratch
If randomize = true, then the frame is filled with Random values.
|
| FrameSplitter |
Frame splitter function to divide given frame into
multiple partitions based on given ratios.
|
| HitRatio | |
| Model<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
A Model models reality (hopefully).
|
| Model.Output |
Model-specific output class.
|
| Model.Parameters |
Model-specific parameter class.
|
| ModelBuilder<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
Model builder parent class.
|
| ModelBuilder.ValidationMessage |
The result of an abnormal Model.Parameter check.
|
| ModelMetrics |
Container to hold the metric for a model as scored on a specific frame.
|
| ModelMetrics.MetricBuilder |
Class used to compute AUCs, CMs & HRs "on the fly" during other passes
over Big Data.
|
| SupervisedModel<M extends Model<M,P,O>,P extends SupervisedModel.SupervisedParameters,O extends SupervisedModel.SupervisedOutput> |
Supervised Model
There is a response column used in training.
|
| SupervisedModel.SupervisedOutput |
Output from all Supervised Models, includes class distribtion
|
| SupervisedModel.SupervisedParameters |
Supervised Model Parameters includes a response column, and whether or
not rebalancing classes is desirable.
|
| SupervisedModelBuilder<M extends SupervisedModel<M,P,O>,P extends SupervisedModel.SupervisedParameters,O extends SupervisedModel.SupervisedOutput> | |
| VarImp | |
| VarImp.VarImpMDA |
Variable importance measured as mean decrease in accuracy.
|
| VarImp.VarImpRI |
Variable importance measured as relative influence.
|
| Enum | Description |
|---|---|
| AUC.ThresholdCriterion | |
| Model.ModelCategory |
Different prediction categories for models.
|
| ModelBuilder.ValidationMessage.MessageType |