[PDF] Top 20 Correlation-based linear discriminant classification for gene expression data.
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Correlation-based linear discriminant classification for gene expression data.
... The Monte Carlo setup was described previously (Kim and Simon, 2011). Simulated datasets were generated using multivariate normal distributions with class-specific mean vectors and common covariance matrices. Each ... See full document
9
ANMM4CBR: a case-based reasoning method for gene expression data classification
... The goal of feature selection is to identify informative genes from thousands of available genes. The informa- tive genes are those that have high discriminative powers, and have low correlations between each pair of ... See full document
11
Recognition of face images using Canonical collection
... sized data sets using existing methods exploiting canonical ...set classification. Specifically, inspired by classical Linear Discriminant Analysis (LDA), we develop a linear ... See full document
7
Revisit linear regression based deconvolution methods for tumor gene expression data
... conclusions based on data normalization ...and data, because the normalization of the total infiltrates to sum to 1 does not apply to TIMER ...Spearman correlation conditioning on tumor purity ... See full document
5
Biclustering of Gene Expression Data by Correlation-Based Scatter Search
... is based on the sum of the squared residues which measure how adequate each expression value is, in com- parison with the rest of values of the bicluster (see [9] for more ...simple linear model for ... See full document
17
Boulesteix, Anne-Laure (2005): Dimension reduction and Classification with High-Dimensional Microarray Data. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... In classification interaction structures among predictors may be used explicitly or im- ...In linear discriminant analysis or logistic regression a familiar way to exploit interactions is the ... See full document
116
Gene Selection and Classification Using Linear Support Vector Machine Based On Microarray Data
... and classification System using Gene Expression ...array expression data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of ... See full document
6
Discriminant Analysis for Human Arm Motion Prediction and Classifying
... system based on Linear Discriminant Analysis (LDA) algorithm for the classification of up- per arm motions; where this algorithm was mainly used in face recognition and voice ...the ... See full document
6
Relevance Vector Machine Classification of Hyperspectral Data Based on Principal Component Analysis and Linear Discriminant Analysis
... hyperspectral data is a three-dimensional image, which can provide both spatial information and spectral ...Hyperspectral data is used in a wide array of applications, such as mining, oil industries, ... See full document
9
Application of Sparse Bayesian Generalized Linear Model to Gene Expression Data for Classification of Prostate Cancer Subtypes
... literature based method called Geneset Cohesion Analysis Tool (GCAT) ...of gene sets based on latent semantic analysis of Medline abstracts ...genes based on the p-value rank ordering of ... See full document
10
Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data
... cancer based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification ...of linear ... See full document
8
Linear Discriminant Analysis based Hybrid SVM-CART for Intrusion Detection System
... that classification is one of the mainly important tasks for different function such as text classification, tone recognition, image classification, micro-array gene expression, ... See full document
7
Hybrid Correlation based Gene Selection for Accurate Cancer Classification of Gene Expression Data
... For finding hybrid negative correlated features, we choose all features genes which are high correlated with IFVc1 from three feature selection techniques then same process is repeated f[r] ... See full document
6
Face Recognition and Verification: A Literature Review
... the data space (observed variables) to the smaller intrinsic dimensionality of feature space (independent variables), which are needed to describe the data economically in ―Face Recognition using Principle ... See full document
7
HOUGH TRANSFORM BASED BROWNBOOST FISHER LINEAR DISCRIMINANT HYPER-SPECTRAL AERIAL IMAGE CLASSIFICATION
... fisher linear discriminant classifier is employed to identify the linear combination of hyper-spectral image features ...fisher linear discriminant classifier provides better ability to ... See full document
8
Gene subset selection for lung cancer classification using a multi-objective strategy
... Keywords: Cancer Classification, Genetic Algorithm, Gene Expression Data, Gene Selection,.. Multi-objective.[r] ... See full document
7
Classification of Cancer Gene Subtypes from Clustering of Gene Expression Data
... microarray gene expression data obscure imperative information which is necessary for the understanding of molecular biology processes that occurs in a specific organism with respect to its ... See full document
5
Linear Maps with Point Rules: Applications to Pattern Classification and Associative Memory
... generalised linear discriminant functions. Clearly, if an error is made in the decision process, then the classification is irretrievably in error. The associative me[r] ... See full document
369
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
... the classification models by malignancy categories as well as on all normal ...the classification rate, calculated as the percentage of tumors. A data point in the upper left corner corresponds to ... See full document
6
Human Face Recognition
... Performance of a face recognition system is reliable and promising when tested on a large group of subjects. Having more subjects in the dataset causes more inter-class similarities and can challenge the feature ... See full document
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