Consider a small dataset with five variables including the target attribute.

Variable #$1$ Variable #$2$ Variable #$3$ Variable #$4$ Target variable

$1$ High High Yes Target $1$

$2$ High High Yes Target $1$

$3$ High High No Target $2$

$4$ Low High Yes Target $1$

$5$ High High Yes Target $1$

$6$ High High Yes Target $1$

$7$ High Low No Target $2$

$8$ High High No Target $2$

$9$ High High Yes Target $1$

$10$ Low High Yes Target $2$

Construct a decision tree from the given data to answer the question 'how two target classes can be differentiated?$\text{'}.$ Use the simple heuristic based on 'the number of instances that can split the dataset into homogenous subsets', as introduced in the lecture, for finding a node and growing the decision tree.

Report the decision tree in the form of decision rules, where each rule shows a branch in the tree. Clearly show all rule conditions $($variable values$)$ and the class they belong to$.$