Top 5 Advantages and Disadvantages of Decision Tree | Types, Pros and Cons, Benefits and Drawbacks

Advantages and disadvantages of Decision Tree: A Decision tree is a Diagram that is used by analysts to decide the outcome of any process that is usually a favourable result. It is a flow chart-like structure that provides the algorithm with decision-making steps with the controlled statement. A decision tree helps people to choose the various decision-making option. We can create it simply by hand or by using specific software.

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What is a Decision Tree? Advantages and Disadvantages of Decision Tree 2022

A Decision Tree is a graphical representation or diagram of a problem with different possible outcomes or results. It is useful in making decisions when we have various possibilities of outcome and looking at the decision tree, we can choose the favourable result process. The main benefit of a decision tree is that it is easy to understand and follow. The basic structure of a Decision tree starts with the root node, leaf node, and branches. Every node comes with two or more possibilities for the problem, which makes the situation easier to understand with choosing the best outcome. It can be smaller in size and also sometimes a little bigger and more complex according to the problem or situation.

Types of Decision Tree

There are two types of Decision trees, they are:

Categorical variable decision tree: A categorical variable decision tree make categorical target variables that are divided the nodes into two categories that give options like yes or No. Generally, in this, every stage falls into yes, but No is in between the node. Mostly it gives a series of nodes that provide choices in Yes and No.

Continuous variable decision tree: Continuous variable decision tree is a tree that uses continuous target variables to predict data output. If we want to calculate the price of any material, then we have to calculate it by including other factors that affect the price of the material and then it continues by keeping the base price which was firstly calculated then various factors new price variability.

Now let us discuss the various Advnatagesof the Decision tree.

Advantages and Disadvantages of Decision Tree 2

Advantages of a Decision Tree

A decision tree is needed when we want to make a decision on a particular problem and it helps to show the clear calculation and possibility of the outcome. So it is very useful in many ways. Here are some Advantages of the Decision Tree

  • Easy to create: A decision tree is easy to create as compared to other algorithms. Using the raw data collocation, we can simply create the decision tree with its decision-making nodes and come to an outcome.
  • Easy to Understand: A Decision tree is a very simple representation and thus it is easy to understand by anyone. If the person does not work in  AI (Artificial Intelligence) then also it is easy for them to understand the changes and outcomes.
  • Data cleaning reduced: The Decision tree is made with very little data and is also easy to make and understand, so unnecessary data collection is avoided. Ths the cleaning of data is reduced.
  • Data exploration: It is one of the best ways to understand the factors and variables that are included in the calculation and helps in decision making by exploring the various factors and data input. Thus it allows the exploration of all the changing variables.
  • Used for Nonlinear relationships: One of the big advantages of the decision tree is that it is also helpful in dealing with nonlinear relationships.
  • Less preparation of Data: with very little data, the decision can be created because it does not require any external data in the making.

These were some of the advantages of a Decision tree which shows the decision tree is easy to create and understand using less amount of data.

Disadvantages of Decision Tree

Some disadvantages of a Decision Tree are as follows

  • Unstable Nature: A decision tree structure is usually get affected by the change in the small data. So it is unstable in nature and cannot be totally dependable.
  • Inaccurate: It can be inaccurate if the variable data is changing often thus, the outcome comes differently every time if we are dealing with variable change. Thus we can not totally rely on it.
  • Complex with new input: It gets complex with adding the new input and the outcome can be more making it complex.
  • Time Taking: For a small tree, it is easy and can be in little time, but if the inputs are more, then it is more time-consuming as compared to other methods.

These were the few disadvantages of the decision tree.

Comparison Table for Advantages and Disadvantages of Decision Tree

Advantages of Decision TreeDisadvantages of Decision Tree
It is easy to createUnstable in nature
It helps decision making and understanding easilyGet complex with new input
Reduces data cleaningInaccurate with new more input change
Data can be exploredTime-consuming
Can be used for the non-linear relationshipLess effective in continuous variable outcome

Advantages and Disadvantages of Decision Tree 1

FAQs on Pros and Cons of Decision tree

Question 1.
What is a Decision Tree? What are its types?

Answer:
A Decision tree is a Diagram that analysts use to decide the outcome of any process that is usually a favourable result.  It is useful in making decisions when we have various possibilities of outcome and looking at the decision tree, we can choose the favourable result process. It can be smaller in size and also sometimes a little bigger and more complex according to the problem or situation.

Two types of Decision trees are:

  • Categorical variable decision tree: A categorical variable decision tree makes categorical target variables that are divided the nodes into two categories that give options like yes or No.
  • Continuous variable decision tree: Continuous variable decision tree is a tree that uses continuous target variables to predict data output with changing input linked to results.

Question 2.
What are the advantages of a Decision Tree?

Answer:
A decision tree is needed when we want to make a decision on a particular problem and it helps to show the clear calculation and possibility of the outcome. So it is very useful in many ways. Here are some Advantages of the Decision Tree

  • It is easy to create with few inputs.
  • Easy to understand.
  • Data cleaning is reduced due to the use of fewer data.
  • Data exploration can be done with the variable that is included and changed.
  • Can also be used for non-linear relationships.
  • Less preparation of data is needed and thus can be made with fewer inputs.

Question 3.
How to create a decision tree?

Answer:
Here are the steps to create a decision tree:

  1. Start the tree by making the first root node in a rectangular shape and write the main criteria or problem which will lead to an outcome.
  2. Now add the branch nodes by entering the basic input.
  3. Add leaves nodes that are more in the tree in which all the questions or criteria are included.
  4. Again, adding more branches means more possibilities for the decision outcome.
  5. Continue the process until all possibilities are added.
  6. In the end, consult and take the decision.

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