AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
The Banker

Banks and regulators clash over ‘black box’ AI credit risk

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...
IEEE

Overview of use of decision tree algorithms in machine learning

Abstract: A decision tree is a tree whose internal nodes can be taken as tests (on input data patterns) and whose leaf nodes can be taken as categories (of these patterns). These tests are filtered ...
IEEE

Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets

Abstract: Decision-tree induction algorithms are widely used in machine learning applications in which the goal is to extract knowledge from data and present it in a graphically intuitive way. The ...
Nature

The data analysis of sports training by ID3 decision tree algorithm and deep learning

In order to improve the accuracy and efficiency of sports training data analysis, this paper proposes an optimized analysis model by combining Iterative Dichotomiser 3 (ID3) decision tree algorithm ...
Analytics Insight

Decision Trees vs. Random Forest: Which Algorithm to Choose?

Choosing the right algorithm for machine learning can make a huge difference in making your model very effective. Of many algorithms, two popular choices have been Decision Trees and Random Forests ...
LinkedIn

Understanding Machine Learning Algorithms: Training Time and Inference Time Complexity

Machine learning (ML) algorithms are at the core of many modern technologies, from recommendation systems to self-driving cars. One of the key factors that determine the efficiency and scalability of ...
Analytics Insight

What is the space complexity of various machine learning algorithms?

Space complexity of machine learning algorithms is the amount of memory or storage an algorithm requires for its successful execution. This becomes one of the important metrics of concern since it ...
Visual Studio Magazine

Decision Tree Regression from Scratch Using C#

Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...
Wired

Google DeepMind CEO Demis Hassabis Says Its Next Algorithm Will Eclipse ChatGPT

In 2016, an artificial intelligence program called AlphaGo from Google’s DeepMind AI lab made history by defeating a champion player of the board game Go. Now Demis Hassabis, DeepMind’s cofounder and ...
InfoWorld

14 popular AI algorithms and their uses

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...