Читать книгу Fundamentals and Methods of Machine and Deep Learning - Pradeep Singh - Страница 21

Decision tree groups are dependent on the element values. They utilize the strategy for Information Gain and discover which element in the dataset, give the best of data, making it a root node, etc., till they can arrange each case of the dataset. Each branch in the decision tree speaks to an element of the dataset [4, 5]. They are one of the most generally utilized calculations for classification. An analysis of the decision tree, the decision tree is utilized to visually and signify the decision and the process of decision making. As the term suggests it utilizes a tree-like representation of choices. Tree models are the objective variable that can take a discrete arrangement of values termed as classification trees; in this tree model, leaves signify the class labels, and combinations of features of class labels are signified by the branches.

Consider an example of listing the students eligible for the placement drive. Now, the scenario is whether the student can attend the drive or not? There are “n” different deciding factors, which has to be investigated for appropriate decision. The decision factors are whether the student has qualified the grade, what is the cut-off, whether the candidate has cleared the test, and so on. Thus, the decision tree model has the following constituents. Figure 1.5 depicts the decision tree model [2]:

Figure 1.5 Decision tree.

 • Root Node: The root node in this example is the “grade”.

 • Internal Node: The intermediate nodes with an incoming edge and more than 2 outgoing edge.

 • Leaf Node: The node without an out-going edge; also known as a terminal node.

For the currently developed decision tree in this example, initially, the test condition from the root hub is tested and consigns the control to one of the active edges; thus, the condition is again tried and a hub is allocated. The tree is supposed to be ended when all the test conditions lead to a leaf hub. The leaf hub consists of class-labels, which vote against or in favor of the choice.