BIOENGINEER

Kernel-Tuned Machine Learning Pushes Network Intrusion Detection Toward 99% Accuracy on Benchmark Data

A new study reports that Random Forest and Gaussian and Sigmoid kernel Support Vector Machines, combined with systematic ...
BIOENGINEER

Research report: A proposed hybrid machine learning and physics-based optimization framework for energy-efficient smart buildings

A hybrid framework combining machine learning, physics-based thermal modelling and optimization achieved up to 26.4 percent ...
ascopubs.org

Python-based preprocessing for applying machine learning in breast cancer metastasis prediction.

To determine correlation of inter reader variability in sum of diameters using RECIST 1.1 with end point assessment in lung cancer. A systematic evaluation of models predicting short-term mortality ...

How Do Machine Learning Models Learn? An Overview from Data Preparation to Training, Evaluation, and Prediction

When you start learning machine learning, you encounter many terms such as "features," "loss functions," "gradient descent," ...
Nature

Feature Selection Techniques in Machine Learning Systems articles from across Nature Portfolio

Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...
techtarget

KDD in data mining assists data prep for machine learning

A machine learning application's value is dependent on the quality of data used to train and deploy it. Organizations are responsible for creating or acquiring enough data, that this data is useful ...