BIOENGINEER

Machine Learning Outperforms Design Codes at Predicting Concrete Crack Spacing

Extremely randomized trees models trained on 96 experimental records predicted primary crack spacing in reinforced concrete ...
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 ...
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 ...
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 ...

Label Design in Financial Machine Learning: Triple Barrier Method, Meta-Labeling, and Pitfalls of Prediction Accuracy

In quantitative trading research, a significant amount of time is spent on model architecture, feature engineering, and ...

3 English Books That Helped Me Get Started with MLOps

Introduction When I first deployed a machine learning model to production, the accuracy on my notebook was sufficient, but ...
techtarget

Clean data is the foundation of machine learning

Machine learning projects can succeed or fail based on a single, seemingly simple factor: data quality. Data scientists and engineers have recognized -- often through hard-won lessons -- that this ...