Search Results - (( java implementation learning algorithm ) OR ( using classes mining algorithm ))
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1
Tree-based contrast subspace mining method
Published 2020“…Mining contrast subspace finds subsets of features or subspaces where a query object is most likely similar to target class against other class in a multidimensional data set of two classes. …”
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Thesis -
2
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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3
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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4
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…When the data is imbalanced, these algorithms generate models that achieve good classification accuracy for the majority class, but poor accuracy for the minority class. …”
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7
Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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8
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Among all these techniques, classification is one of the most commonly used tasks in data mining, which is used by many researchers to classify instances into two or more pre-determined classes. …”
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9
IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property
Published 2016“…In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. …”
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Book Chapter -
10
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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11
Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…Most TC algorithms used terms in representing the document which does not consider the relations among the terms. …”
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12
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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13
Genetic Algorithm for Web Data Mining
Published 2001“…By doing so, it could assist the process of data mining for information in the World Wide Web. This study used a prototype program based on genetic algorithm to manipulate the initial set of data. …”
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Project Paper Report -
14
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Future research includes exploring the use of separator Database in PrefixSpan with pseudoprojection to improve mining generalized sequential patterns, particularly in handling mining constrained sequential patterns.…”
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15
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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16
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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17
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Future research includes exploring the use of separator Database in PrefixSpan with pseudoprojection to improve mining generalized sequential patterns, particularly in handling mining constrained sequential patterns.…”
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18
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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19
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…This research has proven that the TIP method has shown the ability to cater for different kinds of datasets and obtained a good rough classification model with promising results as compared with other commonly used classifiers. This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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20
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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