ML Assignment ML Assignment Q1 What Is SVM Explain With Diagram Q2 What Is Decision Tree

Q1 What is SVM? Explain with diagram.

Q2 What is decision tree? Explain with suitable example and diagram.

A1: Support Vector Machine or SVM is one of the most popular Supervised Learning algorithms, which is used for Classification as well as Regression problems. However, primarily, it is used for Classification problems in Machine Learning.

The goal of the SVM algorithm is to create the best line or decision boundary that can segregate n-dimensional space into classes so that we can easily put the new data point in the correct category in the future. This best decision boundary is called a hyperplane.

SVM chooses the extreme points/vectors that help in creating the hyperplane. These extreme cases are called as support vectors, and hence algorithm is termed as Support Vector Machine. Consider the below diagram in which there are two different categories that are classified using a decision boundary or hyperplane:

A2: A decision tree is a map of the possible outcomes of a
series of related choices. It allows an individual or
organization to weigh possible actions against one another
based on their costs, probabilities, and benefits. They can can
be used either to drive informal discussion or to map out an
algorithm that predicts the best choice mathematically.
A decision tree typically starts with a single node, which
branches into possible outcomes. Each of those outcomes
leads to additional nodes, which branch off into other
possibilities. This gives it a treelike shape.
There are three different types of nodes: chance nodes,
decision nodes, and end nodes. A chance node, represented
by a circle, shows the probabilities of certain results. A
decision node, represented by a square, shows a decision to
be made, and an end node shows the final outcome of a
decision path.
Ideally, a decision tree can be used in almost every sector. This is because we can take any real-world or hypothetical instance and represent it using a decision tree diagram. To further understand what a decision tree is, let’s consider this example. It asks a simple question – whether to buy a new software or not. If we buy a new tool, then it further leads to the comparison between the two options. If not, then we can either continue using the present software or borrow a friend’s tool.