In addition, our work suggests a new specially designed clustering algorithm adapted to the request for comparison of the various COVID time-series of different countries.doi:10.1016/j.dib.2020.105787Vasilios ZarikasStavros G. PoulopoulosZoe Gareiou...
Clustering is a well-known technique for the analysis of Functional Magnetic Resonance Imaging (fMRI) data, whose main advantage is certainly flexibility: ... B Thirion,O Faugeras - 《Medical Image Analysis》 被引量: 61发表: 2004年 An adaptive incremental approach to constructing ensemble classifi...
Data clustering is an essential step in the arrangement of a correct and throughout data model. To fulfill an analysis, the volume of information should be sorted out according to the commonalities. The main question is, what commonality parameter provides the best results – and what is implica...
Data mining tools for Salmonella characterization: application to gel-based fingerprinting analysis The distance matrix and two-way hierarchical cluster analysis tools allow users to directly visualize the similarities/dissimilarities of any two individual ... W Zou,H Tang,W Zhao,... - 《Bmc Bioinfor...
Furthermore, a new parametric model based on content clustering analysis is proposed and validated on our dataset as a benchmark for future research. 展开 关键词: HEVC Objective evaluation techniques Subjective evaluation techniques Video Quality Assessment Bit rate estimation MOS UHD ...
Fatigue Feature Extraction Analysis based on a K-Means Clustering Approach This paper focuses on clustering analysis using a K-means approach for fatigue feature dataset extraction. The aim of this study is to group the dataset as closely as possible (homogeneity) for the scattered dataset. Kurtosi...
FaceNet: A Unified Embedding for Face Recognition and Clustering Despite significant recent advances in the field of face recognition, implementing face verification and recognition efficiently at scale presents serious ... F Schroff,D Kalenichenko,J Philbin - IEEE 被引量: 2049发表: 2015年 Deep ...
This functionisusefulforremoving batch effects,associatedwithhybridization time or other technical variables,prior to clustering or unsupervised analysis suchasPCA,MDS or heatmaps.The design matrixisused to describe comparisons between the samples,forexample treatment effects,which should not be removed.The...
Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine learning (ML) techniques have become an indispensable tool for discovering new drug combinations, the data
We explain one of the possible usages of this dataset by clustering armies on their compositions. This reduction of armies compositions to mixtures of Gaussian allow for strategic reasoning at the level of the components. We evaluated this clustering method by predicting the outcomes of battles ...