Binned Performance

Calculates various performance measures (detailed below) on the input table. This node also takes a column to bin the values on, for example bin on a probability column into 5 bins of: 0.5 ... 0.6, 0.6 ... 0.7, 0.7 ... 0.8, 0.8 ... 0.9 and 0.9 ... 1.0. The min value of the first bin is inclusive and the min value is exclusive for all other bins. All ranges are inclusive of the max value.

Calculates:

Balanced accuracy: Sensitivity + Specificity / 2

Accuracy: TP + TN / 2

Sensitivity: TP / (TP + FN)

Specificity: TN / (TN + FP)

Precision aka Positive Predictivity (PPV): TP / (TP + FP)

Negative predictivity (NPV):TN / (TN + FN)

Recall: TP / (TP + FN)

F-Measure 2 * ((precision * recall) / (precision + recall))

Also outputs the counts for TP, FP, TN, FN, number of equivocals and number of out of domains and coverage (% not out of domain).

Note that the number of equivocals and number out of domain do not impact on the Cooper statistics (Sensitivity, specificity etc.)

Target values that do not match the active or inactive value specified are not included in the calculation.

Options

Binning column: Column which binning should be applied to
Target column: True/experimental activity
Prediction column: Predicted activity
Active (positive) string: String value that represents active
Inactive (negative) string: String value that represents inactive
Equivocal string: String value that represents an equivocal result (prediction only)
Out of domain string: String value that represents a compound which is out of the model's domain
Number of bins: How many bins to create
Range min: The minimum value for the range. If Fail on range issues is checked this must be equal to or smaller than the domain min.
Range max: The maximum value for the range. If Fail on range issues is checked this must be equal to or greater than the domain max.
Fail on range issues: If true then the node will fail to run if the domain of the column falls outside the min and max of the specified range. If you are running in a loop the domain may change, if you want the node to run and output the erroneous rows to the second output uncheck this value. You can also uncheck the value if you only want to use a subset of the range covered in a table.

Input Ports

: Table containing at least the binning column, activity and prediction.

Output Ports

: Row containing all the calculated measures per bin
: A row may fail because of a missing value or a value outside the binning range. These rows are output in this table.

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Installation

To use this node in KNIME, install the extension Lhasa public plugin from the below update site following our NodePit Product and Node Installation Guide:

v5.9

Plugin provider: Lhasa Limited

Plugin version: 2.2.1.v202511242342

On NodePit since: 2025-12-12

Last update: 2026-01-19

Tags: Streamable

KNIME versions: Since v3.6

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