• Corpus ID: 54577415

Improving classification performance of microarray analysis by feature selection and feature extraction methods

@inproceedings{Sun2016ImprovingCP,
  title={Improving classification performance of microarray analysis by feature selection and feature extraction methods},
  author={Jing Sun},
  year={2016}
}
  • Jing Sun
  • Published 26 October 2016
  • Computer Science

Tables from this paper

References

SHOWING 1-10 OF 74 REFERENCES

Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy

This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).

Analysis of a complex of statistical variables into principal components.

Principal component analysis

Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter‐correlated quantitative dependent variables. Its goal is

On Estimation of a Probability Density Function and Mode

Abstract : Given a sequence of independent identically distributed random variables with a common probability density function, the problem of the estimation of a probability density function and of

An overtraining-resistant stochastic modeling method for pattern recognition

We will introduce a generic approach for solving problems in pattern recognition based on the synthesis of accurate multiclass discriminators from large numbers of very inaccurate weak models through

Analysis of Approximation Methods for Differential and Integral Equations

I: Presentation of Numerical Methods.- 1. Finite-Difference Methods for Boundary-Value Problems.- 1.1. Sample Problems.- 1.2. Finite-Difference Methods for Linear, Second Order Ordinary Differential

Partial least-squares regression: a tutorial

Computational Biology and Bioinformatics: Gene Regulation

A comparative study on gene ranking and classification methods using microarray gene expression profiles

A comparative study on different gene ranking methods by applying them to two datasets to demonstrate the importance of informative gene ranking to classify test samples accurately.
...