TriSig: Assessing the statistical significance of triclusters

L Alexandre, RS Costa, R Henriques - arXiv preprint arXiv:2306.00643, 2023 - arxiv.org
Tensor data analysis allows researchers to uncover novel patterns and relationships that
cannot be obtained from matrix data alone. The information inferred from the patterns …

[HTML][HTML] TriSig: Evaluating the statistical significance of triclusters

L Alexandre, RS Costa, R Henriques - Pattern Recognition, 2024 - Elsevier
Tensor data analysis allows researchers to uncover novel patterns and relationships that
cannot be obtained from tabular data alone. The information inferred from multi-way patterns …

TRIQ: a new method to evaluate triclusters

D Gutiérrez-Avilés, R Giráldez, FJ Gil-Cumbreras… - BioData mining, 2018 - Springer
Background Triclustering has shown to be a valuable tool for the analysis of microarray data
since its appearance as an improvement of classical clustering and biclustering techniques …

Artificial Intelligence Techniques Based on K-MeansTwo Way Clustering and Greedy Triclustering Approach for 3D Gene Expression Data (GED)

N Narmadha, R Rathipriya - Artificial Intelligence in Medical Virology, 2023 - Springer
Artificial intelligence (AI) refers to a machine's or robot's capacity to carry out operations that
would typically require human comprehension and intelligence. Classification algorithms …

[PDF][PDF] Tri-clustering from closer property using suffix forest

S Lahiri - 2019 - 20.198.91.3
Abstract Faculty of Engineering Technology Department of Information Technology Master of
Engineering by Sanghamitra Lahiri One can observe a huge change among forests in …

[引用][C] TrLab: una metodología para la extracción y evaluación de patrones de comportamiento de grandes volúmenes de datos biológicos dependientes del tiempo

[引用][C] Greedy Two Way K-Means Clustering For Optimal Coherent Tricluster

N Narmadha, R Rathipriya - Int. J. Sci. Technol. Res, 2019