Stebėti
Professor Zahid Islam
Professor Zahid Islam
Associate Dean (Research), Charles Sturt University
Patvirtintas el. paštas csu.edu.au - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
A hybrid clustering technique combining a novel genetic algorithm with K-Means
MA Rahman, MZ Islam
Knowledge-Based Systems 71, 345-365, 2014
2682014
Software Defect Prediction Using a Cost Sensitive Decision Forest and Voting
M Siers, MZ Islam
Information Systems 51, 62-71, 2015
2002015
Missing Value Imputation Using Decision Trees and Decision Forests by Splitting and Merging Records: Two Novel Techniques
MG Rahman, MZ Islam
Knowledge-Based Systems 53, 51 - 65, 2013
1792013
Comparing sets of patterns with the Jaccard index
S Fletcher, MZ Islam
Australasian Journal of Information Systems 22, 2018
1752018
Decision Tree Classification with Differential Privacy: A Survey
S Fletcher, MZ Islam
ACM Computing Surveys 52 (4), 83:1 - 83:33, 2019
1662019
A decision tree-based missing value imputation technique for data pre-processing
MG Rahman, MZ Islam
The 9th Australasian Data Mining Conference: AusDM 2011, 41-50, 2011
1562011
Privacy preserving data mining: A noise addition framework using a novel clustering technique
MZ Islam, L Brankovic
Knowledge-Based Systems 24 (8), 1214-1223, 2011
1392011
Forest PA: Constructing a Decision Forest by Penalizing Attributes used in Previous Trees
MN Adnan, MZ Islam
Expert Systems with Applications (ESWA), 2017
1322017
Missing Value Imputation using a Fuzzy Clustering Based EM Approach
MG Rahman, MZ Islam
Knowledge and Information Systems 46 (2), 389-422, 2015
1262015
Differentially Private Random Decision Forests using Smooth Sensitivity
S Fletcher, MZ Islam
Expert Systems with Applications (ESWA) 78, 16-31, 2016
1132016
Knowledge discovery through SysFor: a systematically developed forest of multiple decision trees
Z Islam, H Giggins
Proceedings of the Ninth Australasian Data Mining Conference-Volume 121, 195-204, 2011
1032011
Combining k-means and a genetic algorithm through a novel arrangement of genetic operators for high quality clustering
MZ Islam, V Estivill-Castro, MA Rahman, T Bossomaier
Expert Systems with Applications 91, 402-417, 2018
982018
Detecting Autism Spectrum Disorder using Machine Learning Techniques: An Experimental Analysis on Toddler, Child, Adolescent and Adult Datasets
D Hossain, MA Kabir, A Adnan, MZ Islam
Health Information Science and Systems, 2021
972021
Advantages and limitations of genetic algorithms for clustering records
AH Beg, MZ Islam
2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA …, 2016
872016
Optimizing the number of trees in a decision forest to discover a subforest with high ensemble accuracy using a genetic algorithm
MN Adnan, MZ Islam
Knowledge-Based Systems 110, 86-97, 2016
862016
Fimus: A framework for imputing missing values using co-appearance, correlation and similarity analysis
MG Rahman, MZ Islam
Knowledge-Based Systems 56, 311-327, 2014
792014
Privacy-preserving data mining
L Brankovic, MZ Islam, H Giggins
Security, Privacy, and Trust in Modern Data Management, 151-165, 2007
78*2007
Machine Learning in Precision Aggriculture: A Survey on Trends, Applications and Evaluations over Two Decades
S Condran, M Bewong, MZ Islam, L Maphosa, L Zheng
IEEE Access 10, 73786-73803, 2022
752022
A novel quick seizure detection and localization through brain data mining on ECoG dataset
MK Siddiqui, MZ Islam, MA Kabir
Neural Computing and Applications 31, 5595-5608, 2019
612019
A Differentially Private Decision Forest
S Fletcher, MZ Islam
In Proc. of the 13th Australasian Data Mining Conference (AusDM 15), 2015
612015
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Straipsniai 1–20