🥳 RAPIDMINER 9.9 IS OUT!!! 🥳
The updates in 9.9 power advanced use cases and offer productivity enhancements for users who prefer to code.
I have a data set I'm trying to find the natural clusters in. I am using KNN to group the clusters and a Bayesian model to classify the cluster labels
The aim being the higher the accuracy of the Bayesian model, the better the clusters are (There will obviously be some manual checking done afterwards)
I embedded all of this information into an Optimize Parameters as well as a log file to tell me the performance of each iteration i.e. For every value of K output the performance of the model
I got the results below from the log file
K Value Performance
it can be seen from this that the optimal value are 3 or 6. Its possible the Optimize Parameters setting ignored these because of overfitting. It recommended k = 2 with the results below
accuracy: 99.92% +/- 0.02% (mikro: 99.92%)
|true cluster_0 true cluster_1 class precision|
|pred.cluster_0 34792 0 100.00%|
|pred.cluster_1 75 55576 99.87%|
|class recall 99.78% 100.00%|
The accuracy that is shown from the Optimize Parameters is the same as k=3
From the log operator where k = 2 the accuracy is just over 95%
I was wondering if anyone can help me understand why this may be the case?