Data Miner
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The following tables list the members exposed by TKNearestNeighbors.
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Name |
Description |
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Called by LearnData method and K-NN to browse through the learn dataset. | |
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Called by LearnData method and K-NN to browse through the learn data set. | |
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Called by LearnData method and K-NN to restore the current position of the dataset. | |
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Called by LearnData method and K-NN to save the current position of the dataset. |
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Name |
Description |
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Copies the attribute Enabled fields from Source. | |
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Returns an array of attribute indexes sorted by quality. | |
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Get the name of the class at Index. | |
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Determine the most probable class to which the example with values of discrete attributes in DiscreteRecord and values of real valued attributes in FloatRecord belongs to. | |
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Determine the response of all classe for the example with values of discrete attributes in DiscreteRecord and values of real valued attributes in FloatRecord. | |
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Performs the classification on the test data, by calling the OnClassifyTest event. | |
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Get the index of the class with Name. | |
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Clear all learned data and all class descriptions. | |
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Create the component. | |
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This is Destroy, a member of class TKNearestNeighbors. | |
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Disable real valued and discrete attributes for all classes. | |
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Disable discrete attributes for all classes. | |
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Disable real valued attributes for all classes. | |
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Enable real valued and discrete attributes for all classes. | |
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Enable discrete attributes for all classes. | |
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Enable real valued attributes for all classes. | |
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Insert a record holding in to the K nearest neighbors array. | |
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Learn a new record belonging to class with ClassName. | |
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Call this method to perform the learn operation on the learn data. | |
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Learn a new record belonging to class with ClassIndex. | |
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Load the component from file named FileName. | |
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Load the component from stream. | |
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Returns the index of the class, which has the highest count of examples and thus the highest prior probability, with ClassIndex. | |
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Returns numerical representation of MissingFloatValue. | |
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Pruning disables some attributes, to improve classification accuracy. | |
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Pruning disables some attributes, to improve classificaiton accuracy. | |
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Performs pre-pruning and post-pruning and enables only those attributes giving best classification accuracy towards the test dataset. | |
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Reset all learned data including attribute weights and attribute Enabled fields, but keep the class descriptions. | |
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Save the component to file named FileName. | |
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Save the component to stream. | |
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Reset all learned data except attribute weights and attribute Enabled fields and keep the class descriptions. | |
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Sort an array of TIndexRecords. |
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Name |
Description |
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Set the value at index to True/False, to enable/disable the corresponding attribute. | |
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A list of recognized classes. | |
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Called by LearnData method and K-NN to request the positioning to the first record. | |
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Called by LearnData method and K-NN when the last record is fetched. | |
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If the response of all classes is below RejectProbability the example will not be classified to any of the known classes. |
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Name |
Description |
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Called by PrePrune, PostPrune and Prune methods and ClassifyTest methods. |
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Name |
Description |
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Total number of attributes. | |
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Total number of discrete valued attributes or fields holding discreting values in the dataset. | |
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Defines the distance model used, when calculating the distance between examples. | |
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Total number of learned examples. | |
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Total number of real valued attributes or fields holding real values in the dataset. | |
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Set to True, if Class indexes are zero based. | |
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Defines the K parameter for the K-NN algorithm. | |
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Set the value of this property to the index of the example that you want to be ignored during the classification. | |
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Specifies the value indicating a "missing value" (no entry) for discrete attributes in the dataset. | |
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Specifies the value indicating a "missing value" (no entry) for real valued attributes in the dataset. | |
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If true, the number of attributes compared will be normalized between comparisons. | |
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Set this property to true, to store all learned examples. |
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