Scorer (JavaScript)

Compares two columns by their attribute value pairs and shows the confusion matrix, i.e. how many rows of a given attribute and its classification match. 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 view of the node displays three tables, the first one is the confusion matrix with the number of matches in each cell. Row and column rates can be shown via a configuration setting; they are the number of correct predictions divided by the total number of records in the row/column. Additionally, it is possible to highlight cells of this matrix to select the underlying rows. The selection can be passed to other JavaScript views. The second table reports a number of statistics specific to a given class such as True-Positives, False-Positives, True-Negatives, False-Negatives, Accuracy, Balanced Accuracy, Error Rate, False Negative Rate, Recall, Precision, Sensitivity, Specificity, F-measure. The last table contains overall statistics like the Overall Accuracy, Overall Error, Cohen's kappa, the Correctly Classified and the Incorrectly Classified values. These three tables are also available as output ports of this node.

The node supports custom CSS styling. You can simply put CSS rules into a single string and set it as a flow variable 'customCSS' in the node configuration dialog. You will find the list of available classes and their description on our documentation page.

Options

Scorer Options

Title: The view title
Subtitle: The view subtitle
Actual column: The actual column contains the actual classes of the data.
Predicted column: The predicted column contains the predicted classes of the data.
Sorting Strategy: Whether to sort the labels according to their appearance, or use the lexical/numeric ordering.
Reverse order: Reverse the order of the elements.
Ignore missing values: Choose how to treat missing values in either the reference or prediction column. Default is to ignore them (treat them as if the row did not exist). Alternatively, you can expect the table to not contain missing values in these two columns. If they do, the node will fail during execution.
Header color: Background color used for the header sections of the tables (rows or column headers).
Diagonal color: Background color used for highlighting the values on the diagonal of the confusion matrix (the correct predictions).
Display table headers: Check to display the "confusion matrix", "class statistics" and "overall statistics" labels.
Display class nature: Check to display the class nature (Actual or Predicted).
Display number of rows: Check to display the total number of rows in the top left corner of the confusion matrix.
Display float values as percentages: Check to display non-integer values as percentages.
Display confusion matrix rates: Check to display the confusion matrix's rows and columns totals as rates. These are the result of the division of the number of correct predictions on a given row (or cell) divided by the sum of all values on that row or column.
Display fullscreen button: Check to display a button which switches the view into fullscreen mode. The button is only available in the KNIME WebPortal.
Show warnings in view: If checked, warning messages will be displayed in the view when they occur.

Statistics Options

Display class statistics table: Check to display the class statistics table.
Calculate/display true positives for each class: Check to display the true positives in the class statistics table.
Calculate/display false positives for each class: Check to display the false positives in the class statistics table.
Calculate/display true negatives for each class: Check to display the true negatives in the class statistics table.
Calculate/display false negatives for each class: Check to display the false negatives in the class statistics table.
Calculate/display accuracy for each class: Check to display the accuracy in the class statistics table.
Calculate/display balanced accuracy for each class: Check to display the balanced accuracy in the class statistics table.
Calculate/display error rate for each class: Check to display the error rate in the class statistics table.
Calculate/display false negative rate for each class: Check to display the false negative rate in the class statistics table.
Calculate/display recall for each class: Check to display the recall in the class statistics table.
Calculate/display precision for each class: Check to display the precision in the class statistics table.
Calculate/display sensitivity for each class: Check to display the sensitivity in the class statistics table.
Calculate/display specificity rate for each class: Check to display the specificity in the class statistics table.
Calculate/display F-measure for each class: Check to display the F-measure in the class statistics table.
Display overall statistics table: Check to display the overall statistics table.
Calculate/display overall accuracy: Check to display the overall accuracy in the overall statistics table.
Calculate/display overall error: Check to display the overall error in the overall statistics table.
Calculate/display Cohen's kappa: Check to display the Cohen's kappa in the overall statistics table.
Calculate/display number of correctly classified values: Check to display the number of correctly classified values in the overall statistics table.
Calculate/display number of incorrectly classified values: Check to display the number of incorrectly classified values in the overall statistics table.

Control Options

Enable view edit controls: Check to enable controls of the interactive menu in the chart.
Enable title edit controls: Check to enable the editing of the title within the view.
Enable subtitle edit controls: Check to enable the editing of the subtitle within the view.
Enable display table headers toggle: Check to enable the toggling of the display of the table headers.
Enable display rows number toggle: Check to enable the toggling of the display of the rows number.
Enable display confusion matrix rates toggle: Check to enable the toggling of the display of the Confusion Matrix's rows and columns totals as rates.
Enable display class statistics table toggle: Check to enable the toggling of the display of the class statistics table.
Enable display overall statistics table toggle: Check to enable the toggling of the display of the overall statistics table.

Input Ports

: Table containing at least two columns to compare.

Output Ports

: The confusion matrix
: The class statistics table
: The overall statistics table

Popular Predecessors

Popular Successors

Views

Interactive View: Confusion Matrix

Workflows

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

Installation

To use this node in KNIME, install the extension KNIME JavaScript Views (Labs) from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081534

On NodePit since: 2024-07-09

Last update: 2024-11-20

KNIME versions: Since v3.6

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!