Discussing the article: "Data Science and Machine Learning (Part 16): A Refreshing Look at Decision Trees"
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Check out the new article: Data Science and Machine Learning (Part 16): A Refreshing Look at Decision Trees.
Dive into the intricate world of decision trees in the latest installment of our Data Science and Machine Learning series. Tailored for traders seeking strategic insights, this article serves as a comprehensive recap, shedding light on the powerful role decision trees play in the analysis of market trends. Explore the roots and branches of these algorithmic trees, unlocking their potential to enhance your trading decisions. Join us for a refreshing perspective on decision trees and discover how they can be your allies in navigating the complexities of financial markets.
I wrote an article on decision trees in this article series that explained what decision trees are all about, and we built an algorithm to help us classify the weather data. However, the code and explanations provided in the article weren't concise enough; as I keep getting requests to provide a better approach to building decision trees, I believe writing a second article and providing better code for the decision tree might be better. Clarifying the decision trees will make it easier to understand the random forest algorithms that an article is coming out shortly.
Having shown that, let us observe how everything works in action, how to build the tree, and how to use it to make predictions on training and testing, not to mention during real-time trading. We will use the most popular iris-CSV dataset to test if it does work.
Author: Omega J Msigwa