MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
I have just read the original paper proposing PrequentialCV. I found the code here does not seem to follow the paper. For k-fold distributed cross-validation, it should be "Test only one". Meanwhile, k-fold distributed split validation should be "Test all except one". Also, the original code fragment tested all classifier copies despite the validation methodology chosen. This also does not seem to follow the original paper. I just wonder if anything in the code neeeded to be correct, or maybe I misunderstood the code?
I have just read the original paper proposing PrequentialCV. I found the code here does not seem to follow the paper. For k-fold distributed cross-validation, it should be "Test only one". Meanwhile, k-fold distributed split validation should be "Test all except one". Also, the original code fragment tested all classifier copies despite the validation methodology chosen. This also does not seem to follow the original paper. I just wonder if anything in the code neeeded to be correct, or maybe I misunderstood the code?