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