Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Feature selection of gene expression data for cancer classification using double RBF-kernels
Background Using knowledge-based interpretation to analyze omics data can not only
obtain essential information regarding various biological processes, but also reflect the …
obtain essential information regarding various biological processes, but also reflect the …
Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data
Cancer is a severe condition of uncontrolled cell division that results in a tumor formation
that spreads to other tissues of the body. Therefore, the development of new medication and …
that spreads to other tissues of the body. Therefore, the development of new medication and …
Fuzzy co-clustering of documents and keywords
Conventional clustering algorithms such as K-means and SAHN (also known as AHC) have
been well studied and used in the information retrieval community for clustering text …
been well studied and used in the information retrieval community for clustering text …
Fundamentals of fuzzy clustering
Clustering is an unsupervised learning task that aims at decomposing a given set of objects
into subgroups or clusters based on similarity. The goal is to divide the data-set in such a …
into subgroups or clusters based on similarity. The goal is to divide the data-set in such a …
Visual assessment of clustering tendency for rectangular dissimilarity matrices
We have an m times n matrix D, and assume that its entries correspond to pair wise
dissimilarities between m row objects O r and n column objects O c, which, taken together …
dissimilarities between m row objects O r and n column objects O c, which, taken together …
Fuzzy clustering
In this chapter, we show an organic and systematic overview of fuzzy clustering techniques.
In particular, we analyze the mathematical and computational aspects of Fuzzy c-Means …
In particular, we analyze the mathematical and computational aspects of Fuzzy c-Means …
Clustering and aggregation of relational data with applications to image database categorization
In this paper, we introduce a new algorithm for clustering and aggregating relational data
(CARD). We assume that data is available in a relational form, where we only have …
(CARD). We assume that data is available in a relational form, where we only have …
[HTML][HTML] A kernel-based clustering method for gene selection with gene expression data
H Chen, Y Zhang, I Gutman - Journal of biomedical informatics, 2016 - Elsevier
Gene selection is important for cancer classification based on gene expression data,
because of high dimensionality and small sample size. In this paper, we present a new gene …
because of high dimensionality and small sample size. In this paper, we present a new gene …
Simultaneous clustering and dynamic keyword weighting for text documents
In this chapter, we propose a new approach to unsupervised text document categorization
based on a coupled process of clustering and cluster-dependent keyword weighting. The …
based on a coupled process of clustering and cluster-dependent keyword weighting. The …
Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data
D Xu, J Zhang, H Xu, Y Zhang, W Chen, R Gao… - BMC genomics, 2020 - Springer
Background The small number of samples and the curse of dimensionality hamper the better
application of deep learning techniques for disease classification. Additionally, the …
application of deep learning techniques for disease classification. Additionally, the …