Search Results - (( developing function method algorithm ) OR ( data classification methods algorithm ))
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1
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. …”
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Article -
2
Logistic regression methods for classification of imbalanced data sets
Published 2012“…Hence, it is required to develop effective imbalanced LR-based methods to be widely used in data mining applications. …”
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Thesis -
3
Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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4
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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5
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The classification performance varies based on the dataset velocity and the algorithm selection. …”
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6
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The problem of classifying protein sequences based on the primary sequence information is a very complex and challenging task in the analysis and understanding of sequenced data. The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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Conference or Workshop Item -
7
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The problem of classifying protein sequences based on the primary sequence information is a very complex and challenging task in the analysis and understanding of sequenced data. The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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Conference or Workshop Item -
8
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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9
Jogging activity recognition using k-NN algorithm
Published 2022“…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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Academic Exercise -
10
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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11
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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12
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…Wavelet is a mathematical function that decomposes any given data signals and enabling the extraction of discontinuities and sharp spikes permeated in the signal. …”
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Final Year Project / Dissertation / Thesis -
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
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14
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Several approaches and benchmark data were used to validate the effectiveness of the proposed method compared to the unimodal system and normal feature selection method. …”
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15
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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16
Enhancement of new smooth support vector machines for classification problems
Published 2011“…The results of this study showed that MKS-SSVM was effective to diagnose medical dataset and this is promising results compared to the previously reported results. SSVM algorithms are developed for binary classification. …”
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17
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. …”
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18
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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19
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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20
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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