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How to train an artificial intelligence (AI) model, no experience necessary

A recent study shows that 1 in 5 people use AI every day. From the chatbot helping you budget smarter to the recommendations ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Pew Research Center

Americans’ Social Media Use 2025

To better understand which social media platforms Americans use, Pew Research Center surveyed 5,022 U.S. adults from Feb. 5 to June 18, 2025. SSRS conducted this National Public Opinion Reference ...
Yahoo

This Number System Beats Binary, But Most Computers Can’t Use It

The Babylonians used separate combinations of two symbols to represent every single number from 1 to 59. That sounds pretty confusing, doesn’t it? Our decimal system seems simple by comparison, with ...
The New York Times

Everyone Is Using A.I. for Everything. Is That Bad?

Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...
IEEE

Comparative Analysis of Sparse Multinomial Logistic Regression and Convolutional Neural Networks for Multi-Class Image Classification

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
Scientific Research Publishing

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Scientific Research Publishing

Zaidi, A. and Al Luhayb, A.S.M. (2023) Two Statistical Approaches to Justify the Use of the Logistic Function in Binary Logistic Regression. Mathematical Problems in ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...
Visual Studio Magazine

Naive Bayes Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...
IEEE

Comparison of some Logistic Regression Methodologies in Supervised Classification for Functional Data

Abstract: Logistic regression for functional data is a statistical technique for modeling the relationship between functional predictor variables and a binary or multiclass outcome variable. The model ...