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Hace 20 horas · Choosing the right clustering algorithm for categorical data is crucial for effective analysis. While traditional methods like K-Means and DBSCAN are designe...
Hace 1 día · Traditional algorithm for clustering employs the entirety of the feature space dimensions, often leading to suboptimal results due to irrelevant and redundant attributes. Author introduces two novel methods: GA-FS Clustering (utilizing Genetic Algorithm for feature selection) and COSA-Clustering (clustering based on a subset of attributes) tailored for clustering high-dimensional data.
Hace 1 día · Nava Whiteford. May 28, 2024. ∙ Paid. Share. A while back I looked at patterned flow cell IP from PacBio which seemed like it might relate to the Onso. At that time, I was also trying to figure out exactly which amplification approach was being used. While it has difficult be 100% confident, it seemed like the most likely candidate was RCA ...
Hace 4 días · Detailed Description. This section documents OpenCV's interface to the FLANN library. FLANN (Fast Library for Approximate Nearest Neighbors) is a library that contains a collection of algorithms optimized for fast nearest neighbor search in large datasets and for high dimensional features. More information about FLANN can be found in [200] .
Hace 5 días · Single-cell RNA sequencing (scRNA-seq) technology provides a means for studying biology from a cellular perspective. The fundamental goal of scRNA-seq data analysis is to discriminate single-cell types using unsupervised clustering. Few single-cell clustering algorithms have taken into account both deep and surface information, despite the ...
