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Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

“…To remedy this problem, we propose to integrate Principal Component analysis (PCA) which is useful for dimensionality reduction of a dataset with the k-means clustering algorithm. …”
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Improved nu-support vector regression algorithm based on principal component analysis by Abdullah Mohammed, Rashid, Habshah, Midi

“…This paper focuses on improving the nu-SVR algorithm to handle the problem of outliers. A new hybrid PCA with the nu-SVR technique (PCA-SVR) has been established. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…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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Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…Several approaches have been devoted to study such problems using linear and non-linear classification rules, but limited to group imbalance rather than the combination of both problems. …”
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The performance of k-means clustering method based on robust principal components by Kadom, Ahmed, Midi, Habshah, Rana, Sohel

“…To remedy this problem, we proposed to integrate robust principal component analysis (RPCA) with the k-means algorithm. …”
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Improved robust principal component analysis based on minimum regularized covariance determinant for the detection of high leverage points in high dimensional data by Habshah Midi, Jaaz Suhaiza, Mohd Aslam, Hani Syahida, Emi Amielda

“…However, the MRCD-PCA algorithm is quite cumbersome and required longer computational running time. …”
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Evaluating integrated weight linear method to class imbalanced learning in video data by Mohd Apandi, Ziti Fariha, Mustapha, Norwati, Affendey, Lilly Suriani

“…In the second phase, the reduces instances are refined using the weight linear algorithm. The experiment results using 9 soccer video demonstrate that the integration of PCA and WL is capable to alleviates the imbalanced problem and able to improve classification performance in video data.…”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

“…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
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Towards Practical Face Recognition System Employing Row-Based Distance Method In 2dpca Based Algorithms by Al-Arashi, Waled Hussein Mohammed

“…One of the most important extensions of PCA is Two-dimensional PCA (2DPCA). However, 2DPCA-based features are matrices rather than vectors as in PCA. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Improved robust principal component analysis based on minimum regularized covariance determinant for the detection of high leverage points in high dimensional data (penambahbaikan... by Midi, Habshah, Suhaiza, Jaaz, Mohd Aslam, ., Hani Syahida, ., Emi Amielda, .

“…However, the MRCD-PCA algorithm is quite cumbersome and required longer computational running time. …”
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Detection and Severity Identification of control valve stiction in industrial loops using integrated partially retrained CNN-PCA frameworks by YAU, YONG SONG

“…In this thesis, an integrated framework using such partially retrained convolutional neural networks in conjunction with principal component analysis (CNN-PCA) is proposed for simultaneous control valve stiction detection and automatic identification of the severity of the problem. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…This project will study the applicability of the combined algorithm for history matching problem. The study conducted on PCA and RLS method shows high chances of success in applying these methods for history matching problem. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data by Siti Zahariah, Midi, Habshah

“…A simulation study and two real data sets are used to illustrate the merit of our proposed method compared to the RMD-MRCD and Robust PCA (ROBPCA) methods. …”
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Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

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Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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