Improvement on Response Performance of Min-Max Modular Classifier by Symmetric Module Selection
نویسندگان
چکیده
This paper aims to improve the response performance of min-max modular classifier by a module selection policy for two-class classification during recognition. We propose an efficient base classifier selection algorithm. We show that the quadratic complexity of original min-max modular classifier can fall onto the level of linear complexity in the number of base-classifier modules for each input sample under presented selection scheme. The experimental results indicate the effectiveness of our algorithm and verify our theoretical analysis.
منابع مشابه
Module Combination based on Decision Tree in Min-max Modular Network
The Min-Max Modular (M3) Network is the convention solution method to large-scale and complex classification problems. We propose a new module combination strategy using a decision tree for the min-max modular network. Compared with min-max module combination method and its component classifier selection algorithms, the decision tree method has lower time complexity in prediction and better gen...
متن کاملA New Hybrid Framework for Filter based Feature Selection using Information Gain and Symmetric Uncertainty (TECHNICAL NOTE)
Feature selection is a pre-processing technique used for eliminating the irrelevant and redundant features which results in enhancing the performance of the classifiers. When a dataset contains more irrelevant and redundant features, it fails to increase the accuracy and also reduces the performance of the classifiers. To avoid them, this paper presents a new hybrid feature selection method usi...
متن کاملTypical Sample Selection and Redundancy Reduction for Min-Max Modular Network with GZC Function
The min-max modular neural network with Gaussian zerocrossing function (M-GZC) has locally tuned response characteristic and emergent incremental learning ability, but it suffers from high storage requirement. This paper presents a new algorithm, called Enhanced Threshold Incremental Check (ETIC), which can select representative samples from new training data set and can prune redundant modules...
متن کاملUpper and lower bounds of symmetric division deg index
Symmetric Division Deg index is one of the 148 discrete Adriatic indices that showed good predictive properties on the testing sets provided by International Academy of Mathematical Chemistry. Symmetric Division Deg index is defined by $$ SDD(G) = sumE left( frac{min{d_u,d_v}}{max{d_u,d_v}} + frac{max{d_u,d_v}}{min{d_u,d_v}} right), $$ where $d_i$ is the degree of vertex $i$ in graph $G$. In th...
متن کاملStrategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)
In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment ev...
متن کامل