Search Results - (( associative classification techniques algorithm ) OR ( java application testing algorithm ))
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1
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Implementation of the techniques with ID3 algorithm is being discussed thoroughly.…”
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2
An enhanced feature selection technique for classification of group based holy Quran verses
Published 2018“…However, the major setbacks with the existing feature selection techniques are high computational runtime associated with wrapper-based FS techniques and low classification accuracy performance associated with filter-based FS techniques. …”
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3
Ant colony algorithm for web page classification
Published 2008“…Ant Miner II is the used algorithm. It also propose a simple text preprocessing technique to reduce the large numbers of attributes associated with web content mining, without dealing linguistic complications. …”
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4
An enhanced feature selection technique for classification of group-based holy quran verses
Published 2018“…However, the major setbacks with the existing feature selection techniques are high computational runtime associated with wrapper-based FS techniques and low classification accuracy performance associated with filter-based FS techniques. …”
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5
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…Automatic diagnostic methods were frequently used to conduct breast cancer diagnoses in order to increase the accuracy and speed of detection. The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. …”
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6
A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization
Published 2018“…The noisy data affected support value of an itemset and so it influenced the performance of an associative classification. The performance of associative classification is relied on the classification where the classification is worked based on the class association rules which generated from frequent rule mining process. …”
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7
A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization
Published 2018“…The noisy data affected support value of an itemset and so it influenced the performance of an associative classification. The performance of associative classification is relied on the classification where the classification is worked based on the class association rules which generated from frequent rule mining process. …”
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8
Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…However, only supervised learning techniques have proofed insufficient for malware classification task. …”
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Proceeding Paper -
9
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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10
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
11
Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback
Published 2022“…Several researchers have proposed the use of associative classifier that generates strong associations between features and reveals hidden relationship that can be missed by other classification algorithms. …”
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12
Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Final Year Project -
13
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…The first proposed classification algorithm utilizes a Convolution Neural Network (CNN), in which the number of parameters and layers are reduced significantly, and 96% of classification accuracy is achieved on the ISIC dataset. …”
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14
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…The study continued with other classification technique which is neural network with random weights (NNRW). …”
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15
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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16
Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…The study suggests finding a classifier among the most common kinds of classification algorithms within a combined approach represent in Bayesian, Trees, Rules, Function, and lazy algorithms to automate a better performance of early detection of diseases from the medical datasets. …”
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Conference or Workshop Item -
17
Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms. …”
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18
Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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20
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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