Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
It supports client-wise data partitioning and federated learning with feature selection for high-dimensional tabular datasets like IoT-IDS or spam classification. spambase-fed-bfa.ipynb Federated BFA ...
Hosted on MSN
Hamdan bin Mohammed approves launch of pioneering human-machine collaboration classification system
DUBAI, 16th July 2025 (WAM) -- H.H. Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, Crown Prince of Dubai, Deputy Prime Minister, Minister of Defence, and Chairman of the Board of Trustees of the ...
ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback