I ran the KNN algorithm in the TrainVectorClassifier on my data.
I found that entering a different values of K (number if nearest neighbor) has no effect on the results of classfication ( evaluated by cohen’s kappa ) and the results for different k values are always similar to the results for the k= 32 which is the default k value in otb (I compared it with the results for the different k values in the Weka software’s knn model. In Weka, by changing the k values, the classfication results are changing.).
I guess there is a bug in the software.
I would be grateful if anyone can help to solve this problem. Thank you.