BIOENGINEER

Machine Learning Finds Mixed Dietary Signals in Older Adults’ Predicted Skin Cancer

An interpretable machine-learning study of 3,729 older NHANES participants linked mixed dietary signals with predictions of ...
BIOENGINEER

Machine Learning Model Predicts Catheter Thrombosis Risk in Older Cancer Patients

A machine learning study of 532 older cancer patients with PICCs found that simple logistic regression outperformed complex ...
Nature

Machine learning articles from across Nature Portfolio

Researchers developed NiCLIP, an AI model that decodes cognitive tasks, concepts, and domains from brain activation patterns. Trained on over 23,000 papers, NiCLIP excels at group-level decoding, ...

Terms from Convolution Output Size to Natural Language Processing Vectorization Methods Asked in the 2nd G-Certification Mock Exam

Source: Yoshitaka Tomiyama Published: 2020-03-04 / 44 minutes / 24,000 views Scope: The second in a series of explanations ...
Tech Xplore

AI helps identify drilling regimes with a projected potential increase in drilling speed of up to 68%

Assistant professor Shadfar Davoodi at the Skoltech AI Center has developed an approach for optimizing drilling in ...
Interesting Engineering

72 real-world BMW trips suggest regenerative braking can spare EV battery range

Researchers used data from 72 BMW i3 trips and a lizard-inspired algorithm to improve predictions of EV battery charge and ...
Wall Street Journal

The AI Build-Out Is Becoming the Biggest Economic Bet in U.S. History

The AI build-out is on track to become the biggest economic bet in U.S. history, dwarfing the investments made to fund other huge U.S. infrastructure projects such as the railroads, the highway system ...
KPBS

'Ghost in the Machine' explores AI's roots in eugenics

S1: Welcome in San Diego. It's Jade Hindman on this episode of KPBS Midday Edition. A new documentary from PBS Independent Lens traces the origins of artificial intelligence to eugenics. This is KPBS ...
blog.csdn

python-machine-learning-book 第7章实战：用 Majority Vote、Bagging 与 AdaBoost 构建集成学习模型

本文以 python-machine-learning-book仓库 code/ch07的章节内容为核心，系统讲解集成学习（Ensemble Learning）的三种主流实现路径：多数投票集成（Majority Vote）、Bagging 自助采样集成与 AdaBoost 自适应提升。