COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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K-Means
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KNN
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ANN
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Decision Tree
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Detailed explanation-1: -A decision tree is a graphical representation of all possible solutions to a decision based on certain conditions. On each step or node of a decision tree, used for classification, we try to form a condition on the features to separate all the labels or classes contained in the dataset to the fullest purity.
Detailed explanation-2: -A decision tree is a graphical representation of all the possible solutions to a decision based on certain conditions. Tree models where the target variable can take a finite set of values are called classification trees and target variable can take continuous values (numbers) are called regression trees.
Detailed explanation-3: -A decision tree is a graphical representation of possible solutions to a decision based on certain conditions. It’s called a decision tree because it starts with a single box (or root), which then branches off into a number of solutions, just like a tree.
Detailed explanation-4: -A decision tree is a flowchart-like structure in which each internal node represents a “test” on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes).
Detailed explanation-5: -Decision trees are flowchart graphs or diagrams that explore all of the decision alternatives and their possible outcomes. A decision tree is a tool that can help businesses project possible outcomes to make educated and well-thought-out choices.