PLS Dimension Reduction for Classification with Microarray Data
نویسندگان
چکیده
منابع مشابه
PLS dimension reduction for classification with microarray data.
Partial Least Squares (PLS) dimension reduction is known to give good prediction accuracy in the context of classification with high-dimensional microarray data. In this paper, the classification procedure consisting of PLS dimension reduction and linear discriminant analysis on the new components is compared with some of the best state-of-the-art classification methods. Moreover, a boosting al...
متن کاملPLS dimension reduction for classification of microarray data
PLS dimension reduction is known to give good prediction accuracy in the context of classification with high-dimensional microarray data. In this paper, PLS is compared with some of the best state-of-the-art classification methods. In addition, a simple procedure to choose the number of components is suggested. The connection between PLS dimension reduction and gene selection is examined and a ...
متن کاملDimension reduction for classification with gene expression microarray data.
An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical analysis in such applications is dimension reduction. This paper provides a comparison study of three dimension reduction techniques, namely partial least squares (PLS), sliced inverse regression (SIR) an...
متن کاملDimension Reduction of Microarray Data with Penalized Independent Component Aanalysis
In this paper we propose to use ICA as a dimension reduction technique for microarray data. All microarray studies present a dimensionality challenge to the researcher: the number of dimensions (genes/spots on the microarray) is many times larger than the number of samples, or arrays. Any subsequent analysis must deal with this dimensionality problem by either reducing the dimension of the data...
متن کاملA multiple-filter-GA-SVM method for dimension reduction and classification of DNA-microarray data
The following article proposes a Multiple-Filter by using a genetic algorithm (GA) combined with a support vector machine (SVM) for gene selection and classification of DNA microarray data. The proposed method is designed to select a subset of relevant genes that classify the DNA-microarray data more accurately. First, three traditional statistical methods are used for gene selection. Then diff...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Applications in Genetics and Molecular Biology
سال: 2004
ISSN: 1544-6115
DOI: 10.2202/1544-6115.1075