what is the advantage of using Decision Tree Machine Learning Algorithm

[sunrise100]

Is there any important advantage of using Decision Tree Machine Learning Algorithm.

[Clément_Stenac]

Hi,

Decision Trees are not usually extremely performant Machine Learning algorithms. However, they have one big advantage when it comes to transparency: their decisions are easy to understand and explain. In some use cases and industries, this can be a significant advantage.

If this is not a major point to you, you're probably better with more performant general-purposes algorithms like Random Forests

[sunrise100]

Hi All,

I found a good answer here.

Like any other machine learning algorithm, Decision Tree algorithm has both disadvantages and advantages.

Advantages of Decision Tree algorithm

1. When using Decision tree algorithm it is not necessary to normalize the data.


2. Decision tree algorithm implementation can be done without scaling the data as well.

For more details please check the below post.

https://botbark.com/2019/12/19/top-6-advantages-and-disadvantages-of-decision-tree-algorithm/

[Tim]

Hi @sunrise100 ,

It can happen that in terms of explainability you'd rather opt for a  slightly less performing Decision Tree model over a more performant one.

The decision split logic of a Tree can be visualized in a way that most people can understand, compared to other approaches which don't lend themselves for doing that.

Kind Regards,
Tim Dries 

[storm]

1. Decision trees require less effort for data preparation during pre-processing than other algorithms.
2. A decision tree does not require the normalization of data.
3. A decision tree does not require scaling of data as well.
4. Missing values in the data also do NOT affect the process of building a decision tree to any considerable extent.
5. A Decision tree model is intuitive and easy to explain to technical teams and stakeholders.