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Scorer

Analytics Mining Scoring
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Compares two columns by their attribute value pairs and shows the confusion matrix, i.e. how many rows of which attribute and their classification match. Additionally, it is possible to hilight cells of this matrix to determine the underlying rows. The dialog allows you to select two columns for comparison; the values from the first selected column are represented in the confusion matrix's rows and the values from the second column by the confusion matrix's columns. The output of the node is the confusion matrix with the number of matches in each cell. Additionally, the second out-port reports a number of accuracy statistics such as True-Positives, False-Positives, True-Negatives, False-Negatives, Recall, Precision, Sensitivity, Specificity, F-measure, as well as the overall accuracy and Cohen's kappa .

Node details

Input ports
  1. Type: Table
    Input table
    Table containing at least two columns to compare.
Output ports
  1. Type: Table
    Confusion matrix
    The confusion matrix.
  2. Type: Table
    Accuracy statistics
    The accuracy statistics table.

Extension

The Scorer node is part of this extension:

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