DBSCAN to classify another Dataset with the same Attributes
so my idea was to classify objects with a trained DBSCAN model. So if the object from the testdataset is within or near a cluster from the model its labeled with the cluster and when there is no such cluster for the object it labled as unknown or something else (i think the "?" is the label to go). I used the "Apply Model" operator to do such, but this does not work as intended. It basiclly checks if there is a ID that is the same as in the trainingdataset and if so the Object will be labeled the same cluster as the object from the training set. Basically I try to creat a binominal classifier.
So my question, is ther any possible way to create a process that does the idea, but withot a predictiv operator (tree, k-NN,...)?
My idea was to check every cluster with the "loop cluster" and than try to check every object from the testset to the objects in the cluster (like cluser_0 has 10 obejcts, the test set have 10 objects -> the loop runs 100 times) and compare them with an distance measurment (euclidean distance) and if the result is below a threshhold than the object from the testset will be labled as the cluster it was compared with. The output should be the labeled testdata.
any ideas? and thanks