(I am seeing about 5-10 views a day on the Pipeline Pilot pages, please be so kind to acknowledge / cite my blog when you use these tools and guides)
Why would we want such a thing?
Like with the regression validation parameters, I found that PP lacked a component to calculate correlation coefficients between two properties in the data stream in classification.
Therefore I have written a component to do just that. One of the features I find useful is the option to include a bar chart that displays the values of the calculated properties on a scale between 0 and 1. This allows a quick visual inspection of your model reliability. When applied to the 'KNN classification of Estrogen Antagonists' from the example protocols, it looks like this:
In addition it outputs the parameters in a shaded table:
The component calculates these parameters between two properties. Therefore, when using in external validation of a model, the modeled values have to be pre-calculated.
The component requires that you give the names of the properties carying the measured value, the modeled value and the classes that were modeled. Currently it can only be used in a two class classification. In addition you can choose to also output the original unmodified records through the fail port, while the correlation plot and table are output through the pass port. I have not written a 'how to use' in the help, but will do so next week. In the meantime, the component can be found
here.
Why would we want such a thing?
Like with the regression validation parameters, I found that PP lacked a component to calculate correlation coefficients between two properties in the data stream in classification.
Therefore I have written a component to do just that. One of the features I find useful is the option to include a bar chart that displays the values of the calculated properties on a scale between 0 and 1. This allows a quick visual inspection of your model reliability. When applied to the 'KNN classification of Estrogen Antagonists' from the example protocols, it looks like this:
In addition it outputs the parameters in a shaded table:
The component calculates these parameters between two properties. Therefore, when using in external validation of a model, the modeled values have to be pre-calculated.
The component requires that you give the names of the properties carying the measured value, the modeled value and the classes that were modeled. Currently it can only be used in a two class classification. In addition you can choose to also output the original unmodified records through the fail port, while the correlation plot and table are output through the pass port. I have not written a 'how to use' in the help, but will do so next week. In the meantime, the component can be found
here.
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