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1
An extended ID3 decision tree algorithm for spatial data
Published 2011“…The objective of this paper is to propose a new spatial decision tree algorithm based on the ID3 algorithm for discrete features represented in points, lines and polygons. …”
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2
Case Slicing Technique for Feature Selection
Published 2004“…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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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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A data mining approach to construct graduates employability model in Malaysia
Published 2011“…The performance of Bayes algorithms are also compared against a number of tree-based algorithms. …”
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Using a range flows from 1000 to 100000 with an increment of 10000 flows per step in two network topologies namely, Fat Tree and Simple Tree Topologies, that were created using the Mininet simulator and connected to the Ryu controller, the performance of the proposed algorithms was evaluated for efficiency and effectiveness across a variety of evaluation metrics. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking
Published 2012“…The experimental validations show that the use of Hessian matrix results in significant improvement in the robustness of the tracing algorithm. …”
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9
Optimizing B-tree search performance of big data sets / Mohsen Marjani
Published 2017“…This study proposes an optimized B-tree search method to improve the execution time of the search tasks and to optimize the performance of the B-tree search process. …”
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10
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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11
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The algorithm involved the construction of the nodes of a lexicographic tree that represent frequent patterns. …”
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12
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The second task is to enhance rules accuracy based on the first task, while the third task is to classify new objects or cases. …”
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13
Complex word identification model for lexical simplification in the Malay language for non-native speakers
Published 2023“…This study consists of three modules, i) A Malay CWI dataset, ii) Malay CWI features with the new enhanced stemmer rules, and iii) A CWI model based on the Gradient Boosted Tree (GB) algorithm. …”
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14
The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The methodology is based on JavaScript and PHP languages for developing a new technique called DetectCombined capable of filtering queries using parameterized queries to protect against SQL injection which is a safe method. …”
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Power lines vegetation enchroachment monitoring based on satellite stereo images using stereo matching
Published 2023“…However, these methods are constrained with time consumption and cost. In this paper,a new method based estimating 3D height/depth of vegetation or trees near transmission lines using satellite stereo vision is proposed. …”
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Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Improving mining efficiency: A new scheme for extracting association rules
Published 2009“…Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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