One of the core benefits of clustering is its strength as an unsupervised learning technique. Unlike supervised methods, clustering does not require labeled data, which is often the most time-consuming and expensive aspect of ML. Clustering allows analysts to work directly with raw data and bypasse...
In microbiome data analysis, unsupervised clustering is often used to identify naturally occurring clusters, which can then be assessed for associations with characteristics of interest. In this work, we systematically compared beta diversity and clustering methods commonly used in microbiome analyses. We...
Statistical methods OTU clustering We used Qiime (v1.9.1) and VSEARCH (v1.9.6) to classify and identify the intestinal microbiome. In brief, the process involved the following steps: [1] Unique sequences were extracted from the optimized effective sequences, and the number of repetitions of ...
Machine learning (ML) clustering methods stand in contrast to generative models and their focus on the theoretical origins of clusters. As with many ML applications, it may be possible to achieve good results while entirely ignoring how a particular network was generated. Most approaches seek cluste...
Machine learning (ML) clustering methods stand in contrast to generative models and their focus on the theoretical origins of clusters. As with many ML applications, it may be possible to achieve good results while entirely ignoring how a particular network was generated. Most approaches seek cluste...
(2008) Comparative analysis of clustering methods for microarray data. In: Emmert-Streib F, Dehmer M, editors. Analysis of microarray data: a network-based approach, Weinheim, Germany; Wiley-VCH Verlag GmbH & Co. KGaA; http://dx.doi.org/10. 1002/9783527622818.ch2....
3.2 Clustering methods The clustering method is a subset of unsupervised machine learning algorithms, in which, patterns within a dataset will be identified and the method will automatically generate subgroups of similar types of input variables, also known as clusters [71]. According to this definit...
Methods and Implements of Deep Clustering. Contribute to zhoushengisnoob/DeepClustering development by creating an account on GitHub.
Spatial clustering, which shares an analogy with single-cell clustering, has expanded the scope of tissue physiology studies from cell-centroid to structure-centroid with spatially resolved transcriptomics (SRT) data. Computational methods have undergone
The main goal of our study is to characterize the limits and the overall structure of the immune system variations in a large healthy cohort by leveraging different methods of clustering. In particular, we apply three complementary algorithms, on data gathered from both a base cohort and a repli...