B. Minaei-Bidgoli
Publications
225
h-index
27
Citations
3,135
Highly Influential Citations
114
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Multi objective association rule mining with genetic algorithm without specifying minimum support and minimum confidence
Hamid Reza Qodmanan, M. Nasiri, B. Minaei-Bidgoli
Computer ScienceExpert Syst. Appl.
2011
TLDR
This paper proposes a method based on genetic algorithm without taking the minimum support and confidence into account, and applies the FP-tree algorithm in order to improve algorithm efficiency. Expand
131 Citations
11
Mining numerical association rules via multi-objective genetic algorithms
B. Minaei-Bidgoli, R. Barmaki, M. Nasiri
Mathematics, Computer ScienceInf. Sci.
1 June 2013
TLDR
A multi-objective genetic algorithm approach for mining association rules for numerical data based on the notion of rough patterns that use rough values defined with upper and lower intervals to represent a range or set of values. Expand
89 Citations
8
PDF
Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System
B. Minaei-Bidgoli, W. Punch
Computer Science
GECCO

12 July 2003
TLDR
An approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system is presented and shows that when the number of features is few; feature weighting is works better than just feature selection. Expand
191 Citations
7
PDF
Adaptive clustering ensembles
A. Topchy, B. Minaei-Bidgoli, Anil K. Jain, W. Punch
Mathematics
ICPR

23 August 2004
Clustering ensembles combine multiple partitions of the given data into a single clustering solution of better quality. Inspired by the success of supervised boosting algorithms, we devise an… Expand
105 Citations
6
Cluster ensemble selection based on a new cluster stability measure
H. Alizadeh, B. Minaei-Bidgoli, H. Parvin
Mathematics, Computer ScienceIntell. Data Anal.
1 May 2014
TLDR
A new asymmetric criterion, called the Alizadeh--Parvin--Moshki--Minaei criterion APMM, is proposed to assess the association between a cluster and a set of partitionings and it is shown that the APMM criterion overcomes the deficiency in the conventional NMI measure. Expand
48 Citations
5
PDF
Comparison of Classification Methods Based on the Type of Attributes and Sample Size
Reza Entezari-Maleki, A. Rezaei, B. Minaei-Bidgoli
Mathematics, Computer Science
J. Convergence Inf. Technol.
30 September 2009
TLDR
It can be concluded that in the datasets with few numbers of records, the AUC become deviated and the comparison between classifiers may not do correctly and when the number of the records and theNumber of the attributes in each record are increased, the results become more stable.Expand
98 Citations
5
PDF
To improve the quality of cluster ensembles by selecting a subset of base clusters
H. Alizadeh, B. Minaei-Bidgoli, H. Parvin
Computer ScienceJ. Exp. Theor. Artif. Intell.
2 January 2014
TLDR
A clustering ensemble approach combined with a cluster stability criterion as well as a dataset simplicity criterion is explored to discover the finest subset of base clusters for each kind of datasets. Expand
37 Citations
3
MKNN: Modified K-Nearest Neighbor
H. Parvin, H. Alizadeh, B. Minaei-Bidgoli
Mathematics
2008
In this paper, a new classification method for enhancing the performance of K-Nearest Neighbor is proposed which uses robust neighbors in training data. This new classification method is called… Expand
59 Citations
3
PDF
A clustering ensemble framework based on elite selection of weighted clusters
H. Parvin, B. Minaei-Bidgoli
Mathematics, Computer Science
Adv. Data Anal. Classif.
1 June 2013
TLDR
This paper proposes a weighted locally adaptive clustering (WLAC) algorithm that is based on the LAC algorithm that suffers from sensitivity to its two parameters that should be tuned manually, and proposes two solutions.Expand
44 Citations
3
PDF
PREDICTING STUDENT PERFORMANCE: AN APPLICATION OF DATA MINING METHODS WITH THE EDUCATIONAL WEB-BASED SYSTEM LON-CAPA
B. Minaei-Bidgoli, D. Kashy, G. Kortemeyer, W. Punch
Engineering
2003
Newly developed web-based educational technologies offer researchers unique opportunities to study how students learn and what approaches to learning lead to success. Web-based systems routinely… Expand
123 Citations
3
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