Tag: ensemble learning

Researchers developed TENTACLES, an open-source consensus machine learning framework that extracted reproducible gene signatures across 689 intestinal biopsy samples from ...

Researchers have developed an explainable hybrid intrusion detection framework that combines data balancing, statistical feature selection, and ensemble learning to ...

A new lightweight AI framework integrates deep learning, ensemble methods, and semantic search to classify skin lesions with high accuracy ...

Researchers have developed a collaborative machine learning model that couples valuation forecasting with decision optimization, achieving a 94.7 percent valuation ...

A multicenter retrospective study developed and externally validated a stacking ensemble machine learning model utilizing routine clinical variables to identify ...

A new iterative ensemble learning method estimates tendon loss in prestressed concrete bridges by analyzing vertical deck deflections, offering a ...

A new PSO-BPNN-RF ensemble model improves the accuracy of long-term settlement predictions for airport taxiways under complex traffic loads.

A new meta-learning framework called META-TASC couples uncertainty estimation and calibration with communication-risk scheduling for healthcare-oriented IoT systems, improving waiting ...

Researchers have introduced iAMP-Deep, an alignment-free artificial intelligence framework that combines multimodal sequence embeddings and ensemble learning to discover divergent ...

A stacking ensemble machine learning framework combining three diverse base algorithms and Lasso regression accurately predicts the compressive strength of ...