1. From 'Simulating Humans' to 'Data-Driven': The Ultimate Goal and Implementation Path of AI ...

#DESCRIPTION: This project was developed as part of CodTech Internship Task-1, where I implemented a basic Decision Tree Classifier using Python. The objective was to understand how decision trees ...

#DESCRIPTION: My domain is Machine Learning, and my first task was implementing a Decision Tree. I wrote and executed the code in Google Colab, ensuring it ran correctly and produced the expected ...

This article presents a demo of decision tree regression, implemented from scratch, using the C# language. The concepts underlying decision tree regression are relatively simple, but implementation is ...

Each technique has pros and cons. This article explains how to implement decision tree regression from scratch, using the C# language. Compared to other regression techniques, decision tree regression ...

Conclusion: Our study shows potential implementation of machine learning decision tree model algorithms based on a hierarchical, convenient, and personalized use of perfusion and spectroscopy MRI data ...

Abstract This paper explores the use of soft decision trees [1] in basic reinforcement applications to examine the efficacy of using passive-expert like networks for optimal Q-Value learning on ...