use R package 'modes' to detect bimodality, calculate coefficients and create a chart
You could use that in KNIME and see if you can use the statistics that are provided by this package to make a decision. It also creates a plot where you can visually inspect if there is a Bi-Modal distribution. You might adapt that to test for further distributions.
Please note I am not an expert in these statistics, just built them into a workflow :slight_smile:. The description 9 for the package for example states that for the:
bimodality_coefficient - "The bimodality coefficient has a range of zero to one (that is: [0,1]) where a value greater than “5/9” suggests bimodality. "
So with 0.774 being larger than 0.556 the statistic here would indicate that the distribution is bimodal. And the visual inspection seems to support that.
I was toying around with creating a variable to bring the description into the graphic but gave up for now. You might include that ins some future graphic you might create.
Workflow
R Graphics - use R package modes to detect bimodality, calculate coefficients and create a chart
External resources
- Medium Blog: Exploring the Power of R Graphics with KNIME: A Collection of Examples
- Medium Blog: KNIME and R — installation across operating systems — some remarks
- Hub: more R Graphics with KNIME
- modes-Package, An R package that calculates various mode and modal measures for complex distributions and big data
- Find the Modes and Assess the Modality of Complex and Mixture Distributions, Especially with Big Datasets
- forum entry
Used extensions & nodes
Created with KNIME Analytics Platform version 5.2.2
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