Given the data sets shown in Figures 5.6, explain how the decision tree, naive Bayes, and k-nearest neighbor classifiers would perform on these data sets.
Figures 5.6

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Attributos Attributos shing Attributoa Noise Attributas Distnguishing Attributos Noiso Attrbutos Class A Class A Rooords Rooords ClassB Cass B (a) Synthetic data set 1 (b) Synthetic data set 2 Attrlbutes DistngulshingNolse Atributee Class A Class BClass AClass B Class A Class B ClassA Class B Class A Class B Class A Class B Class A Class B Class A Class B ClassA Class B Class A Class B 60% tiled with 1 | 40% med Class A with ecords 40%nilad with 1 | 60% tied with Class B Attribute X (c) Synthetic data set 3. (d) Synthetic data set 4 Class A Class B Class A Class B Class B Attribute x Attribute X (e) Synthetic data set 5. (f) Synthetic data set 6.