APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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All data holds importance while developing the Decision Tree.
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The beginning point of any Decision Tree is known as its Root.
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Decision Trees is a rule-based AI model which helps the machine in predicting what an element is with the help of various rules.
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None of the above
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Detailed explanation-1: -About Decision Tree. The Decision Tree algorithm, like Naive Bayes, is based on conditional probabilities. Unlike Naive Bayes, decision trees generate rules. A rule is a conditional statement that can easily be understood by humans and easily used within a database to identify a set of records.
Detailed explanation-2: -Decision trees have three main parts: a root node, leaf nodes and branches. The root node is the starting point of the tree, and both root and leaf nodes contain questions or criteria to be answered. Branches are arrows connecting nodes, showing the flow from question to answer.
Detailed explanation-3: -A decision tree is a non-parametric supervised learning algorithm, which is utilized for both classification and regression tasks. It has a hierarchical, tree structure, which consists of a root node, branches, internal nodes and leaf nodes.