In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 34 state-of-the-
The clustering or categorizing is repeated adjusted based on received user input to generate an updated model associating documents with classes. Outlier and. ambiguity measures are also calculated at runtime for new documents classified using the model.ジーン ミッシェル レンダース...
In single-cell RNA-seq data analysis (Fig.1), common steps after HVG detection include cell clustering and differentially expressed gene (DEG) detection. The goal of cell clustering is to identify potential cell types, and subsequent DEG detection aims to find the genes that are significantly mo...
通常前者称为分类,后者称为聚类(clustering),后文中提到的分类都是指有指导的学习过程。 给定分类体系,将文本集中的每个文本分到某个或者某几个类别中,这个过程称为文本分类(text categorization)。将文本集合分组成多个类或簇,使得在同一个簇中的文本内容具有较高的相似度,而不同簇中的文本内容差别较大,这个过...
Methods, systems, and apparatus, including computer program products, for query ranking based on query clustering and categorization, are disclosed. In one aspect, search queries are selected and grouped into one or more clusters. A representative query is selected for each cluster. Each cluster is...
Different from previous document clustering methods based on latent semantic indexing (LSI) or nonnegative matrix factorization (NMF), our method tries to discover both the geometric and discriminating structures of the document space. Theoretical analysis of our method shows that LPI is an ...
In this paper, we call this process as associative categorization, which is different from classical clustering, associative classification and associative clustering. Focusing on representing the associations of behaviors and the corresponding uncertainties, we propose the method for constructing a Markov ...
The term weighting methods assign appropriate weights to the terms to improve the performance of text ategorization. In this study, the investigate several widely-used unsupervised (traditional) and supervised term weighting methods on benchmark data collections in combination with NLP and Clustering ...
Specifically, we examined whether unsupervised clustering provides a useful alternative to supervised clustering in the discovery of meaningful categories when studying the domain of emotion. Our unsupervised clustering methods consistently treat the number of clusters as a statistical parameter to be learned...
between clustering and text categorisation. Clustering is a way to group text according to its character; text categorisation classifies text according to predefined categories (Ishida, 2006). The literature reviewed here adopts a general approach and, as such, treats all of these terms synonymously ...