Search Results - (( based constructive method algorithm ) OR ( based evaluation mining algorithm ))

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  1. 1

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Then, the proposed method is developed based on the architecture such that the mining model is constructed once, and it can be frequently mined by various minsup. …”
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    Thesis
  2. 2

    Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

    Published 2014
    “…The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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    Thesis
  3. 3

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. As a result, time-series clustering (as a part of temporal data mining research) has attracted increasing interest for use in various areas such as medicine, biology, finance, economics, and in the Web. …”
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    Thesis
  4. 4

    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

    Published 2017
    “…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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    Thesis
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    Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin by Nasaruddin, Syazwani

    Published 2017
    “…Activities in this section are, for testing part, 314 words from 2 different speakers are evaluated by using clustering method. WEKA is a set of machine learning algorithm for data mining task. …”
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    Thesis
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    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    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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    Thesis
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    Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review by Ahmad, Rabiah, Abd Hamid, Nazirah, Selamat, Siti Rahayu

    Published 2018
    “…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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    Article
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    An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

    Published 2015
    “…In recent years, data mining based anomaly detection (DMAD), particularly classification methods, have been incessantly enhanced in differentiating normal and attack behaviour. …”
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    Thesis
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
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    A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

    Published 2016
    “…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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    Conference or Workshop Item
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    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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    Final Year Project
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    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob by Yaacob, Siti Hajar

    Published 2014
    “…Besides that, Genetic Algorithm is applying to predict future sales based on the sales and product data. …”
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    Thesis
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    Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

    Published 2018
    “…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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    Article
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    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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    Article
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