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.
This is a companion discussion topic for the original entry at https://kni.me/w/TSnw-_U0Rj2Y97gG