Cluster analysis

Xem 1-20 trên 95 kết quả Cluster analysis
  • Cluster Analysis is a technique for classifying data, i.e to divide the given data into a set of classes or clusters.

    pdf0p ledung 13-03-2009 116 32   Download

  • Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học 'Respiratory Research cung cấp cho các bạn kiến thức về ngành y đề tài: Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation...

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  • Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

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  • This book has its conceptual origin from the lecture materials of the training courses taught by one of the authors in the early nineties. It was during this period that in several developing nations, particularly in Africa, even when the signs of widespread hunger and abject poverty were visible, policy makers did not act for want of ‘empirical evidence’. Some policy makers even dismissed the severity of the problem saying that the hunger reports prepared by government officials were not rigorous enough to take them seriously.

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  • (BQ) Part 2 book "A handbook of applied statistics in pharmacology" presents the following contents: Non-Parametric tests, cluster analysis, trend tests, dose response relationships, analysis of pathology data, designing an animal experiment in pharmacology and toxicology—randomization, determining sample size, how to select an appropriate statistical tool,...

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  • (BQ) Part 2 book "Marketing research" has contents: Sampling fundamentals, sample size and statistical theory, discriminant, factor, and cluster analysis; presenting the results, presenting the results, marketing mix measures,...and other contents.

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  • Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis...

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  • (BQ) Part 2 book "Business research methods" has contents: Questionnaire design; data preparation and preliminary analysis, multiple regression multiple regression; data preparation and preliminary analysis, exploratory factor and principal component analysis, cluster analysis, binary logistic regression, business research reports.

    pdf133p bautroibinhyen23 02-04-2017 5 1   Download

  • Cluster analysis is an unsupervised technique of grouping related objects without considering their label or class. The objects belonging to the same cluster are relatively more homogeneous in comparison with other clusters. The application of cluster analysis is in areas like gene expression analysis, galaxy formation, natural language processing and image segmentation etc.

    pdf12p dieutringuyen 07-06-2017 0 0   Download

  • We explore an approach to possibilistic fuzzy c-means clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. In our experiments we found that in this way we can combine the partitioning property of the probabilistic fuzzy c-means algorithm with the advantages of a possibilistic approach w.r.t.

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  • Learn to implement clustering and load balancing solutions with Windows 2000 and Windows Server 2003, and deliver nearly 100 percent uptime. With a focus on real world production-based problems, the author delivers detailed high availability solutions that will give you the tools to roll out and troubleshoot these technologies.

    pdf401p ken333 14-06-2012 79 21   Download

  • Creates nested clusters Agglomerative clustering algorithms vary in terms of how the proximity of two clusters are computed MIN (single link): susceptible to noise/outliers MAX/GROUP AVERAGE: may not work well with non-globular clusters CURE algorithm tries to handle both problems Often starts with a proximity matrix A type of graph-based algorithm

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  • We describe the early stage of our methodology of knowledge acquisition from technical texts. First, a partial morpho-syntactic analysis is performed to extract "candidate terms". Then, the knowledge engineer, assisted by an automatic clustering tool, builds the "conceptual fields" of the domain. We focus on this conceptual analysis stage, describe the data prepared from the results of the morpho-syntactic analysis and show the results of the clustering module and their interpretation.

    pdf3p bunthai_1 06-05-2013 31 4   Download

  • We describe a strategy for systematic amplification of chitin synthase genes (chs) in the filamentous ascomycetes plant-pathogenBotrytis cinereausing PCR with multiple degen-erate primers designed on specific and conserved sequence motifs. Eight distinctchsgeneswere isolated, namedBcchs I, II, IIIa, IIIb, IV, V, VIandVII. They probably constitute the entire chsmultigenic family of this fungus, as revealed by careful analysis of six euascomycetes genomes.

    pdf12p dell39 03-04-2013 16 3   Download

  • The clinically used beta-lactamase inhibitor clavulanic acid is produced by fermentation of Streptomyces clavuligerus. The orf6 gene of the clavulanic acid biosynthetic gene cluster in S. clavuligerus encodes a protein that shows sequence homology to ornithine acetyltransferase (OAT), the fifth enzyme of the arginine biosynthetic pathway. Orf6 was overexpressed in Escherichia coli (at  15% of total soluble protein by SDS/PAGE analysis) indicating it was not toxic to the host cells. The recombinant protein was purified (to 95% purity) by a one-step technique.

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  • MicroRNAs (miRNAs) have been proven to play important roles at the post-transcriptional level in animals and plants. To investigate clustering patterns and specific sequence characteristics in the flanking regions of plant miRNA genes, we performed genome-wide analyses ofArabidopsis thaliana, Populus trichocarpa, Oryza sativaand Sorghum bicolor.

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  • For languages whose character set is very large and whose orthography does not require spacing between words, such as Japanese, tokenizing and part-of-speech tagging are often the difficult parts of any morphological analysis. For practical systems to tackle this problem, uncontrolled heuristics are primarily used. The use of information on character sorts, however, mitigates this difficulty. This paper presents our method of incorporating character clustering based on mutual information into DecisionTree Dictionary-less morphological analysis.

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  • This article describes GALATEAS LangLog, a system performing Search Log Analysis. LangLog illustrates how NLP technologies can be a powerful support tool for market research even when the source of information is a collection of queries each one consisting of few words. We push the standard Search Log Analysis forward taking into account the semantics of the queries. The main innovation of LangLog is the implementation of two highly customizable components that cluster and classify the queries in the log. ...

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  • Ech hydrogenase fromMethanosarcina barkeriis a member of a distinct group of membrane-bound [NiFe] hydrogenases with sequence similarity to energy-conserving NADH:quinone oxidoreductase (complex I). The sequence of the enzyme predicts the binding of three [4Fe-4S] clusters, one by subunit EchC and two by subunit EchF. Previous studies had shown that two of these clusters could be fully reduced under 10 5 Pa of H2at pH 7 giving rise to two distinct S½ electron paramagnetic resonance (EPR) signals, designated as the g¼1.89 and theg¼1.92 signal....

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  • Focusing on multi-document personal name disambiguation, this paper develops an agglomerative clustering approach to resolving this problem. We start from an analysis of pointwise mutual information between feature and the ambiguous name, which brings about a novel weight computing method for feature in clustering. Then a trade-off measure between within-cluster compactness and among-cluster separation is proposed for stopping clustering. After that, we apply a labeling method to find representative feature for each cluster. ...

    pdf8p hongphan_1 15-04-2013 19 1   Download

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