• No results found

A novel Neuro-fuzzy classification technique for data mining

N/A
N/A
Protected

Academic year: 2021

Share "A novel Neuro-fuzzy classification technique for data mining"

Copied!
19
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Figure 1 Proposed Neuro-fuzzy classification model.
Figure 3 A hidden or output layer unit j of a MLPBPN model.
Figure 4 Broad level steps of the detailed procedure.
Table 3 Detailed accuracy by each class for three classifiers.
+7

References

Related documents

Different studies have shown and used different approach in synthesizing silver nanoparticles where all of them succeed in producing silver nanoparticles,

The purpose of this study was explore whether a model of daily health-related utility using EQ-5D derived data from randomised trials would more accurately reflect quality of

The reduced size of the glint in the image introduces cer- tain indetermination in the position of the corneal reflection and consequently in the corneal center computation. The

In the present study, models of diverse nature have been developed through decision tree (DT), random for- est (RF), support vector machine (SVM), and moving average analysis

The objective of this review, therefore, is to provide an update on the prevalence and the pharmacotherapeutic management of pediatric psoriasis, which could be beneficial

Hence, the present work reports the exact values of elastic properties of graphyne including surface Young’s modulus and Poisson’s ratio.. The analysis is based on DFT

In MacLean, Thorp, Zhao and Ziemba (2009) in this section of this volume, we present simulations of medium term Kelly, fractional Kelly and propor- tional betting strategies..