Document clustering using sample weighting [PDF]
, 2007 Clustering algorithm based on Sample weighting has been noticed recently. In this paper, a novel sample weighting clustering algorithm is presented based on K-Means and fuzzy C-Means algorithm.
Su, Xinning +2 more
core +1 more source
Forward-stagewise clustering: An algorithm for convex clustering [PDF]
Pattern Recognition Letters, 2019 Abstract This paper proposes an exceptionally simple algorithm, called forward-stagewise clustering, for convex clustering. Convex clustering has drawn recent attention since it nicely addresses the instability issue of traditional non-convex clustering methods.
openaire +2 more sources
A Benchmark Suite for Clustering Algorithms – Version 1.0.0
, 2020 This is version 1.0.0 of the benchmark suite, dated 8 May 2020. The contents of this repository are frozen -- no new datasets will be added. This will ensure that everyone evaluates their methods on the same test data.
Marek Gagolewski
core +1 more source
Fuzzy clustering of time series gene expression data with cubic-spline [PDF]
, 2013 Data clustering techniques have been applied to ex- tract information from gene expression data for two decades. A large volume of novel clustering algorithms have been developed and achieved great success.
Ali, Akhtar, Wang, Yu, Angelova, Maia
core +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
MOA: Massive Online Analysis, a framework for stream classification and clustering. [PDF]
, 2010 Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams.
Kranen, Philipp +7 more
core +1 more source
Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics [PDF]
, 2013 Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper,
Muhammad F Bari +24 more
core +2 more sources
Cognitive and Neuroimaging Divergence Between Juvenile and Adult FUS Amyotrophic Lateral Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive motor neuron degeneration. Fused in sarcoma (FUS)‐associated juvenile ALS (jALS) represents a distinct and aggressive subgroup with rapid deterioration and poor prognosis.
Alexandra V. Jürs +7 more
wiley +1 more source
Global Rather Than Vertical‐Selective Saccadic Abnormalities in Progressive Supranuclear Palsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To test whether vertical saccades are preferentially affected in Progressive Supranuclear Palsy (PSP). Methods PSP patients (n = 24) were compared to age‐matched controls (n = 94) and two degenerative groups (Alzheimer's disease, n = 20; Lewy body disease, n = 50).
Duy Duan Nguyen +6 more
wiley +1 more source
Performance comparison of fuzzy and non-fuzzy classification methods
Egyptian Informatics Journal, 2016 In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM), Gustafson–Kessel (GK) and non-fuzzy algorithm, k-means (KM) are most popular ...
B. Simhachalam, G. Ganesan
doaj +1 more source