Search Results - (( java implication based algorithm ) OR ( knowledge evaluation mining algorithm ))
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1
An Improved C4.5 Data Mining Driven Algorithm for the Diagnosis of Coronary Artery Disease
Published 2019“…This research used an im-proved C4.5 data mining algorithm for the diagnosis of CAD. A performance evaluation of the improved algorithm was carried out against the traditional C4.5 Algorithm. …”
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2
An efficient algorithm to discover large and frequent itemset in high dimensional data
Published 2019“…For this reason, this research has proposed two new algorithms; RARE and RARE II, which mine colossal closed itemsets. …”
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Monograph -
3
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Thesis -
4
Improved BVBUC algorithm to discover closed itemsets in long biological datasets
Published 2019“…The task in mining closed frequent itemsets requires the algorithm to mine the frequent ones then determine its closure. …”
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Article -
5
Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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Conference or Workshop Item -
6
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
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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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri
Published 2003“…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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10
Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report
Published 2011“…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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Article -
11
Discovering decision algorithm from a distance relay event report
Published 2009“…In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. …”
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Article -
12
Evaluation and optimization of frequent, closed and maximal association rule based classification
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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Investigation of Data Mining Using Pruned Artificial Neural Network Tree
Published 2008“…A major drawback associated with the use of artificial neural networks for data mining is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the knowledge captured is not transparent and cannot be verified by domain experts. …”
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15
Identifying significant features and data mining techniques in predicting cardiovascular disease / Mohammad Shafenoor Amin
Published 2018“…This raw data is needed to be processed to make certain decision on various information. Data mining turns a large collection of data into knowledge. …”
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Thesis -
16
Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…The performance of the genetic algorithm with 2-satisfiability-based reverse analysis was measured according to the selected performance evaluation metrics. …”
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In the field of computer science, data mining facilitates the extraction of useful knowledge and patterns from a huge amount of data. …”
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Article -
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Thus, data stream clustering is crucial for extracting hidden knowledge and data mining. Various data stream clustering methods have lately been introduced. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…The objective of this study is to propose a prediction model based on bio-inspired algorithm for talent knowledge discovery through some experiments. …”
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Research Reports -
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Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance
Published 2019“…This provides a large corpus of information retrievable for data mining and knowledge discovery. The case study is focused on the investigation of machine breakdown and the effectiveness of scheduled maintenance with the application of data mining. …”
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Monograph
