Algorithm 1( Decision Tree Algorithm) part 1

Hi,

Now let’s dig deeper into Machine Learning with a brief walk-through of some most commonly used Machine Learning algorithms.

Codes, abstract theories will follow sooner since we introduce and remind some based statistic concepts.

I will start by synoptic schemas for my simple pictures illustrating how the chosen algorithms are used.

The first algorithm covered in this post is Decision Tree.

Why do we have to choose Decision trees?

I believe a few which are

1.       It’s so simple to understand the data and make some good interpretations.

2.      Decision trees actually make you see the logic for the data to interpret

Classify data according to some features, whenever the process goes to the next step, there is a judging branch, and the judgment divides the data into two, and the process goes on.

When tests are done with existing data, there is new data coming in, computer can categorize data into the right leaves.

In the next publishing, we will propose for existing data a  very simple decision tree for classification problem.

See you