type TStatisticClassifier = class(TClassifier);
Abstract classifier class for statistical classifiers.
Abstract classifier class for "Naive Bayes" and "Linear Classifier" classification algorithms.
Properties
| Name | Type | Description |
|---|---|---|
| AttributeEnabled | boolean | Set the value at index to True/False, to enable/disable the corresponding attribute. |
| Classes | TClassesList | Pointer to list of classes with attribute descriptions and stored learned data. |
| OnFirstRecord | TNotifyEvent | Called by LearnData method and K-NN to request the positioning to the first record. |
| OnIndexNextRecord | TIndexNextRecord | Called by LearnData method and K-NN to browse through the learn dataset. |
| OnLastRecord | TNotifyEvent | Called by LearnData method and K-NN when the last record is fetched. |
| OnNameNextRecord | TNameNextRecord | Called by LearnData method and K-NN to browse through the learn data set. |
| OnPopPosition | TPopBookmark | Called by LearnData method and K-NN to restore the current position of the dataset. |
| OnPushPosition | TPushBookmark | Called by LearnData method and K-NN to save the current position of the dataset. |
| RejectProbability | double | If the response of all classes is below RejectProbability the example will not be classified to any of the known classes. |
Methods
| Name | Description |
|---|---|
| AssignAttributeState | Copies the attribute Enabled fields from Source. |
| AttributeQuality | Returns an array of attribute indexes sorted by quality. |
| ClassesName | |
| Classify | |
| ClassifyResponse | |
| ClassifyTest | Performs the classification on the test data, by calling the OnClassifyTest event. |
| ClassIndex | |
| Clear | |
| Create | |
| Destroy | |
| DisableAttributes | Disable real valued and discrete attributes for all classes. |
| DisableDiscreteAttributes | Disable discrete attributes for all classes. |
| DisableFloatAttributes | Disable real valued attributes for all classes. |
| EnableAttributes | Enable real valued and discrete attributes for all classes. |
| EnableDiscreteAttributes | Enable discrete attributes for all classes. |
| EnableFloatAttributes | Enable real valued attributes for all classes. |
| Entropy | Returns the average information entropy. |
| Learn | |
| LearnData | Call this method to perform the learn operation on the learn data. |
| LearnIndex | |
| LoadFromFile | Load the component from file named FileName. |
| LoadFromStream | |
| MaxDiscreteEntropy | Returns the maximum entropy of the discrete attribute at AttributeIndex. |
| MaxEntropy | Returns the maximum entropy found to be of the attribute at Index. |
| MaxFloatEntropy | Returns the maximum entropy of the real valued attribute at AttributeIndex. |
| MaxPriorProbability | |
| MissingFloatNumber | Returns numerical representation of MissingFloatValue. |
| PostPrune | Pruning disables some attributes, to improve classification accuracy. |
| PrePrune | Pruning disables some attributes, to improve classificaiton accuracy. |
| Prune | Performs pre-pruning and post-pruning and enables only those attributes giving best classification accuracy towards the test dataset. |
| Reset | |
| SaveToFile | Save the component to file named FileName. |
| SaveToStream | |
| SoftReset | |
| SortIndexRecord | Sort an array of TIndexRecords. |