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- modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly...
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- analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, and nonparametric analysis. A few examples...
- Referenced in 137 articles
- nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project...
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- interpretation and validation of cluster analysis...
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- clustering, and various tools for visual analysis of clustering results...
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- Model-based cluster and discriminant analysis with the MIXMOD software The Mixture Modeling (MIXMOD) program ... purposes of density estimation, clustering or discriminant analysis. A large variety of algorithms to estimate ... suitability depending on the particular perspective (cluster analysis or discriminant analysis). Written in C++, MIXMOD...
- Referenced in 15 articles
- cluster: Cluster Analysis Extended Rousseeuw et al , Cluster Analysis, extended original from Peter Rousseeuw, Anja...
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- general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further ... centroids, ...), and bootstrap methods for the analysis of cluster stability...
- Referenced in 255 articles
- decision processes and continuous-time Markov chains. Analysis is performed through model checking such systems ... randomized distributed algorithms, manufacturing systems and workstation clusters...
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- primarily for scale construction using factor analysis, cluster analysis and reliability analysis, although others provide...
- Referenced in 9 articles
- also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning...
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- boxplots), principal component analysis (using biplots), cluster analysis with Aitchison distance, analysis of variance (ANOVA...
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- specified prior to training. A cluster analysis is first performed on the training data ... through the proper connections of these computed clusters. However, most existing neural fuzzy systems (whether...
- Referenced in 28 articles
- Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest...
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- TreeSOM: cluster analysis in the self-organizing map Clustering problems arise in various domains ... similar elements close together, forming clusters. Cluster analysis is often left to the user ... tools to perform unsupervised SOM cluster analysis, determine cluster confidence and visualize the result...
- Referenced in 16 articles
- primitive: principal component analysis, k means clustering, the Perceptron Algorithm, the ID3 algorithm, and (apparently...
- Referenced in 19 articles
- clustering for multi-way clustering, CuBatch for batch data analysis, indafac for PARAFAC, PARALIND...
- Referenced in 54 articles
- platforms and tens of processors on commodity clusters using gigabit ethernet. NAMD uses the popular ... program VMD for simulation setup and trajectory analysis, but is also file-compatible with AMBER...
- Referenced in 5 articles
- assessing the uncertainty in hierarchical cluster analysis. It provides AU (approximately unbiased) p-values...
- Referenced in 54 articles
- values. Unfortunately, many algorithms for gene expression analysis require a complete matrix of gene array ... input. For example, methods such as hierarchical clustering and K-means clustering are not robust...