You learn a decision tree (DT) and a naïve Bayes (NB) model for a data set and use 10-fold cross validation to evaluate them.  Suppose that DT has higher accuracy than NB on 7 folds and NB has higher accuracy on 3 folds.    a.       Based on this result, is one model clearly better than the other? (Yes / No) b.      How can you verify with confidence which is better?

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Temporal difference learning

Temporal difference learning (TD learning) is a concept in machine learning that attributes to a class of model-free reinforcement learning methods. The technique predicts a reward or quantity depending on the future values of the value function.