K-nearest neighbors (KNN) algorithm is a type of supervised machine learning algorithm which can be used for both classification as well as regression predictive problems. However, it is mainly used for classification predictive problems in industry. The following two properties would define KNN well.
(1) Lazy learning algorithm − KNN is a lazy learning algorithm because it does not have a specialized training phase and uses all the data for training while classification.
(2) Non-parametric learning algorithm − KNN is also a non-parametric learning algorithm because it doesn’t assume anything about the underlying data.
[Distance] = x && [__Product] = EARLIER( [__Product] )
Cartesian product of the training data table and the test data table.
Complete the classification of the test data and return the result table.
"Maximum number of nearby points", MAX('Table'[number of nearby points])
'Table'[number of nearby points], 'Result'[Maximum number of nearby points]
According to the above operations, we can see that KNN algorithm can actually be accomplished by Power BI. But considering the limitations on query performance and the data set size, it is recommended to use Python or R.