Results 101 to 110 of about 559,125 (302)
Identifying optimistic stocks with K-means clustering algorithm
International Review of Economics & FinanceSelecting stocks from a large number of active stocks is a critical and challenging investment decision due to high volatility and biased decision-making.
Bilal Aslam
doaj +1 more source
Fast K-Means Algorithm Clustering
International journal of Computer Networks & Communications, 2011 16 pages, Wimo2011; International Journal of Computer Networks & Communications (IJCNC) Vol.3, No.4, July ...
Raied Salman +4 more
openaire +2 more sources
An efficient k-modes algorithm for clustering categorical datasets
, 2022 Mining clusters from data is an important endeavor in many applications. The k-means method is a popular, efficient, and distribution-free approach for clustering numerical-valued data, but does not apply for categorical-valued observations.
Maitra, Ranjan, Dorman, Karin S.
core
Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +3 more
wiley +1 more source
Molecular Oncology, EarlyView.Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller +10 more
wiley +1 more source
Improved K-Means Algorithm for Nearby Target Localization
IEEE AccessIn a multi-source localization system, direction of arrival (DOA) estimation of angles always suffers from errors due to noise interference, sensor position inaccuracies, and other factors.
Zongwen Yuan +3 more
doaj +1 more source
An Efficient k-modes Algorithm for Clustering Categorical Datasets
, 2020 Mining clusters from datasets is an important endeavor in many applications. The k-means algorithm is a popular and efficient distribution-free approach for clustering numerical-valued data but can not be applied to categorical-valued observations. The k-
Maitra, Ranjan, Dorman, Karin
core
Molecular Oncology, EarlyView.BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi +11 more
wiley +1 more source
Implementation of K-means Clustering Algorithm using Java
, 2011 Emergence of modern techniques for scientific data collection has resulted in large scale accumulation of data pertaining to diverse fields. Conventional database querying methods are inadequate to extract useful information from huge data analysis ...
Prof. S.China Venkateswarlu +2 more
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, 2013 Intrusion Detection System (IDS) is an active defense technology. Many clustering algorithms are used to improve the performance of accuracy and hit rate and reduce False Alarm Rate (FAR).
Zainal, Anazida +7 more
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