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SVD-Based Modeling for Image Texture Classification Using Wavelet Transformation
TLDR
This paper introduces a new model for image texture classification based on wavelet transformation and singular value decomposition that achieves higher recognition rates compared to the traditional subband energy- based approach, the hybrid IMM/SVM approach, and the GGD-based approach. Expand
PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET
TLDR
It is proved that the reduced dataset is performing better than the full featured dataset and the efficiency and False Alarm Rate is measured. Expand
Hierarchical multi-class SVM with ELM kernel for epileptic EEG signal classification
TLDR
The results show that the proposed H-MSVM with ELM kernel is efficient in terms of better classification accuracy at a lesser execution time when compared to ANN, various multi-class SVMs, and other research works which use the same clinical dataset. Expand
Performance analysis of intrusion detection system using various neural network classifiers
TLDR
It is proved that the reduced dataset is performing better than the full featured dataset. Expand
Binary classification of cancer microarray gene expression data using extreme learning machines
TLDR
The results indicate that ELM produces comparable or better results compared to the traditional classification methods like Naïve Bayes, Bagging, Random Forest and Decision Table. Expand
CLASSIFICATION OF BRAIN TISSUES USING MULTIWAVELET TRANSFORMATION AND PROBABILISTIC NEURAL NETWORK
This paper describes a new approach for the classification of brain tissues into White Matter, Gray Matter, Cerebral Spinal Fluid, Glial Matter, Connective and MS lesion in multiple sclerosis. TheExpand
An Optimized Extreme Learning Machine for Epileptic Seizure Detection
TLDR
The performance of the proposed OELM with Wavelet based statistical features is better in terms of training time and classification accuracy and needs less training time compared with SVM. Expand
Image texture classification using wavelet based curve fitting and probabilistic neural network
TLDR
Experimental results prove that the proposed approach gives better classification rate under noisy environment than model based and feature based methods in terms of signal to noise ratio and classification rate. Expand
Detection of Attacks for IDS using Association Rule Mining Algorithm
ABSTRACT Intrusion detection system (IDS) plays a vital role in network infrastructure. Organizations have to protect the data from various attacks which are frequently affecting the networks. InExpand
A Comparative Performance Evaluation of Supervised Feature Selection Algorithms on Microarray Datasets
TLDR
KNN classifier is found to produce higher classifier accuracy compared to traditional classifiers available in literature and fuzzy rough set based feature selection approach is computationally faster and produces lesser number of genes in the reduced subset compared to correlation based filter. Expand
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