Clustering ensembleGenerative mechanismConsensus functionEnsemble memberDiversityEnsemble sizeGraph, a kind of structured data, is widely used to model complex relationships among objects, and has been used in various of scientific and engineering fields, such as bioinformatics, network intrusion detection, ...
To overcome the restrictive linearity assumption, numerous nonlinear approaches were proposed to extend successful subspace clustering approaches to data on a union of nonlinear manifolds. In this comparative study, we provide a comprehensive overview of nonlinear subspace clustering approaches proposed in ...
Virtual clustering analysis (VCA) is a reduced-order method for numerical homogenization. We formulate VCA for finite strain problems, illustrate its implementation, and provide numerical codes for free download and perusal. Comparison for four test examples shows that both VCA and Self-consistent clus...
In this section, the trained machine learning algorithms, which are Multi-Layer Perception, K-Nearest Neighbour, Support Vector Machine, Random Forest, and Adaptive Boosting, are discussed along with the key information of the collected data. Machine learning algorithms Multi-layer perception (MLP) ...
From the past few decades, the popularity of meta-heuristic optimization algorithms is growing compared to deterministic search optimization algorithms in
Nuclear Norm Clustering aims to improve the accuracy of clustering. In this paper, we compared the performance of NNC with that of other seven methods, using 15 publically available datasets. We then tested the performance of NNC on two psoriasis genome-wide association study (GWAS) datasets17,...
cl-online-learning - Online learning algorithms (Perceptron, AROW, SCW, Logistic Regression). cl-random-forest - Implementation of Random Forest in Common Lisp.ClojureNatural Language ProcessingClojure-openNLP - Natural Language Processing in Clojure (opennlp). Infections-clj - Rails-like inflection ...
clustering. The benefit of these methods is that they provide a literature profile (by means of different document representations) for each gene/protein of interest. These profiles are then used to perform further analysis like pair-wise comparisons, clustering or are even combined with experimental...
Title: A benchmark of algorithms for the analysis of pooled CRISPR screens Authors: Sunil Bodapati*, Timothy P. Daley*, et al. Journal Info: Genome Biology, March 2020 Description: This study evaluates and compares various algorithms used for analyzing data from pooled CRISPR screens, using ...
In addition to those k-means refinements, several algorithms have been proposed anew to cluster the points around centroids while avoiding the problems of k-means. Hierarchical clustering algorithms are of relevance for CLUBS+, and come in two flavors: divisive and agglomerative. Divisive clustering ...