Showing 9 of total 9 results (show query)
mhahsler
stream:Infrastructure for Data Stream Mining
A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.
Maintained by Michael Hahsler. Last updated 19 days ago.
data-stream-clusteringdatastreamstream-miningcpp
39 stars 10.05 score 132 scripts 3 dependents
reconhub
epicontacts:Handling, Visualisation and Analysis of Epidemiological Contacts
A collection of tools for representing epidemiological contact data, composed of case line lists and contacts between cases. Also contains procedures for data handling, interactive graphics, and statistics.
Maintained by Finlay Campbell. Last updated 2 months ago.
15 stars 8.68 score 112 scripts 2 dependents
branchlab
metasnf:Meta Clustering with Similarity Network Fusion
Framework to facilitate patient subtyping with similarity network fusion and meta clustering. The similarity network fusion (SNF) algorithm was introduced by Wang et al. (2014) in <doi:10.1038/nmeth.2810>. SNF is a data integration approach that can transform high-dimensional and diverse data types into a single similarity network suitable for clustering with minimal loss of information from each initial data source. The meta clustering approach was introduced by Caruana et al. (2006) in <doi:10.1109/ICDM.2006.103>. Meta clustering involves generating a wide range of cluster solutions by adjusting clustering hyperparameters, then clustering the solutions themselves into a manageable number of qualitatively similar solutions, and finally characterizing representative solutions to find ones that are best for the user's specific context. This package provides a framework to easily transform multi-modal data into a wide range of similarity network fusion-derived cluster solutions as well as to visualize, characterize, and validate those solutions. Core package functionality includes easy customization of distance metrics, clustering algorithms, and SNF hyperparameters to generate diverse clustering solutions; calculation and plotting of associations between features, between patients, and between cluster solutions; and standard cluster validation approaches including resampled measures of cluster stability, standard metrics of cluster quality, and label propagation to evaluate generalizability in unseen data. Associated vignettes guide the user through using the package to identify patient subtypes while adhering to best practices for unsupervised learning.
Maintained by Prashanth S Velayudhan. Last updated 6 days ago.
bioinformaticsclusteringmetaclusteringsnf
8 stars 8.21 score 30 scripts
cbg-ethz
clustNet:Network-Based Clustering
Network-based clustering using a Bayesian network mixture model with optional covariate adjustment.
Maintained by Fritz Bayer. Last updated 1 years ago.
bayesian-networkbayesian-networksclusteringdaggenomicsmixture-modelnetwork-clustering
7 stars 5.16 score 41 scripts
reumandc
wsyn:Wavelet Approaches to Studies of Synchrony in Ecology and Other Fields
Tools for a wavelet-based approach to analyzing spatial synchrony, principally in ecological data. Some tools will be useful for studying community synchrony. See, for instance, Sheppard et al (2016) <doi: 10.1038/NCLIMATE2991>, Sheppard et al (2017) <doi: 10.1051/epjnbp/2017000>, Sheppard et al (2019) <doi: 10.1371/journal.pcbi.1006744>.
Maintained by Daniel C. Reuman. Last updated 3 years ago.
1 stars 4.80 score 125 scripts
cellmapslab
longmixr:Longitudinal Consensus Clustering with 'flexmix'
An adaption of the consensus clustering approach from 'ConsensusClusterPlus' for longitudinal data. The longitudinal data is clustered with flexible mixture models from 'flexmix', while the consensus matrices are hierarchically clustered as in 'ConsensusClusterPlus'. By using the flexibility from 'flexmix' and 'FactoMineR', one can use mixed data types for the clustering.
Maintained by Jonas Hagenberg. Last updated 1 years ago.
3 stars 4.18 score 7 scripts
techtonique
bcn:Boosted Configuration Networks
Boosted Configuration (neural) Networks for supervised learning.
Maintained by T. Moudiki. Last updated 6 months ago.
machine-learningneural-networksstatistical-learningcpp
5 stars 4.00 score 4 scripts
sevvandi
eventstream:Streaming Events and their Early Classification
Implements event extraction and early classification of events in data streams in R. It has the functionality to generate 2-dimensional data streams with events belonging to 2 classes. These events can be extracted and features computed. The event features extracted from incomplete-events can be classified using a partial-observations-classifier (Kandanaarachchi et al. 2018) <doi:10.1371/journal.pone.0236331>.
Maintained by Sevvandi Kandanaarachchi. Last updated 3 years ago.
3 stars 3.18 score
andeek
protoshiny:Interactive Dendrograms for Visualizing Hierarchical Clusters with Prototypes
Shiny app to interactively visualize hierarchical clustering with prototypes. For details on hierarchical clustering with prototypes, see Bien and Tibshirani (2011) <doi:10.1198/jasa.2011.tm10183>. This package currently launches the application.
Maintained by Andee Kaplan. Last updated 3 years ago.
1 stars 2.70 score 4 scripts