• Publications
  • Influence
An Improved Fuzzy Support Vector Machine for Credit Rating
tl;dr
In order to classify data with noises or outliers, Fuzzy support vector machine (FSVM) improve the generalization power of traditional SVM by assigning a fuzzy membership to each data point. Expand
  • 8
  • 2
  • Open Access
An effective discretization method for disposing high-dimensional data
tl;dr
We present a supervised dimension reduction algorithm for data discretization, which effectively maps high-dimensional data into a lower intrinsic dimensional space. Expand
  • 23
A new approach for discretizing continuous attributes in learning systems
tl;dr
In this paper, we propose a novel class-attribute interdependency discretization algorithm (termed as NCAIC), which takes account of data distribution and the interependency between all classes and attributes. Expand
  • 12
The Enumeration of Preimages and Gardens-of-Eden in Sequential Cellular Automata
tl;dr
This paper presents a preimages enumeration formula for a rule in SCA, and gives two methods for enumerating the preimages of a rule. Expand
  • 3
  • Open Access
Fuzzy Support Vector Machine Based on Vague Sets for Credit Assessment
tl;dr
We propose a new FSVM based on vague sets that apply a truth-membership and a false- membership to each data point of training sets. Expand
  • 10
Information discriminative extreme learning machine
tl;dr
We propose a regularized extreme learning machine (algorithm) based on discriminative information (called IELM) that can significantly improve the classification performance and generalization ability of ELM. Expand
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Modifications to Bayesian Rough Set Model and Rough Vague Sets
tl;dr
The variable precision rough set (VPRS) model generalizes the Pawlak rough set model with variable parameters. Expand
  • 3
An Algorithm for Discretization of Real Value Attributes Based on Interval Similarity
tl;dr
Discretization algorithm for real value attributes is of very important uses in many areas such as intelligence and machine learning. Expand
  • 4
  • Open Access
Modifications to Bayesian Rough Set Model and Rough Vague Sets
tl;dr
The variable precision rough set (VPRS) model generalizes the Pawlak rough set model with variable parameters. Expand
  • 2
Quasi-curvature Local Linear Projection and Extreme Learning Machine for nonlinear dimensionality reduction
tl;dr
We present Quasi-curvature LLE (QLLE) through taking the curvature of local neighborhoods into consideration when mapping local configuration into low-dimensional coordinates for nonlinear dimensionality reduction. Expand
  • 3