  We present a reformulation of the regression and classification, which aims
to validate the result of a machine learning algorithm. Our reformulation
simplifies the original problem and validates the result of the machine
learning algorithm using the training data. Since the validation of machine
learning algorithms must always be explainable, we perform our experiments with
the kNN algorithm as well as with an algorithm based on conditional
probabilities, which is proposed in this work. For the evaluation of our
approach, three publicly available data sets were used and three classification
and two regression problems were evaluated. The presented algorithm based on
conditional probabilities is also online capable and requires only a fraction
of memory compared to the kNN algorithm.
