Search Results - (( data (replication OR implication) mining algorithm ) OR ( code classification rules algorithm ))

Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…However, supervised learning technique has limitations for malware classification task. 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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Binary vote assignment on grid quorum replication technique with association rule by Ainul Azila, Che Fauzi

“…The main feature of BV AGQ-AR is that the technique integrates replication and data mining technique allowing meaningful extraction of knowledge from large data sets. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”

Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

“…Fuzzy Logic is used in the classification phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

“…Unique features from the I", 4t h ,7th and 8thl evel details are obtained as criteria for developing a Rules-Based Algorithm for classifying disturbances that have occurred. …”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

“…There are so many forecasting algorithms and techniques available. The abilities of Data Mining to obtain and gather data from multiple sources is very useful to researcher, practitioner, business and more. …”
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Intelligent mining of large-scale bio-data: bioinformatics applications by Hashemi, Farahnaz Sadat Golestan, Ismail, Mohd Razi, Yusop, Mohd Rafii, Hashemi, Mahboobe Sadat Golestan, Shahraki, Mohammad Hossein Nadimi, Rastegari, Hamid, Miah, Gous, Aslani, Farzad

“…It also highlights some future perspectives of data mining in bioinformatics that can inspire further developments of data mining instruments. …”
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Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…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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Organizational Culture Automated Audit System (OCAAS) by Al - Jubair, Md. Abdullah

“…Several state of the art technologies and techniques were used to design and developed OCAAS which include the use of machine learning and sentiment analysis based novel opinion mining algorithms for electronic opinion analysis and computerized statistics based mathematical algorithms for electronic data analysis as well as MySQL database integration for faster data processing and cognitive ergonomics system interface for user friendly interface navigation.…”
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Datasets Size: Effect on Clustering Results by Raheem, Ajiboye Adeleke, Ruzaini, Abdullah Arshah, Hongwu, Qin

“…This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

“…The best algorithm will not be the same for all the data sets. …”
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Smart agriculture economics and engineering: Unveiling the innovation behind ai-enhanced rice farming by Chuan, Zun Liang, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, Chong, Yeh Sai

“…This article introduced innovative Artificial Intelligence-based (AI-based) predictive algorithms for short-term rice production, utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Prediction of diabetic retinopathy among diabetic neuropathy in T2DM patients using data mining algorithm / Nur Balqis Oon ... [et al.] by Oon, Nur Balqis, Khairudin, Zuraida, Abd Rahman, Hezlin Aryani, Kamarudin, Norbaizura, Abu Bakar, Nur Syamimi, Abd Aziz, Nor Azimah

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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming by Zun Liang, Chuan, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, David Lau, King Luen, Chong, Yeh Sai

“…To address these challenges, an innovative Artificial Intelligence-based (AI-based) predictive algorithm has been proposed, leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Application of artificial intelligence (AI) in islamic investments by Haneffa Muchlis Gazali, Junisa Jumadi, Noor Rasyidah Ramlan, Nurmaisarah Abd Rahmat, Siti Nor Hazilawati Mohd Uzair, Amirah Norliyana Mohid

“…The technology helps investors to analyse their stocks in terms of price levels, the current stability of each stock and the future price forecasts based on current price and stock data. The study is a conceptual discussion on the application of AI in Islamic investment, which focuses on the discussion of Text Mining, Algorithmic Trading, Stock Pick and Robo in Investment, which include Robo Advisor, Robo Islamic Advisor (RIA) and Robo Financial Advisor (RFA) operating in Islamic investment system. …”
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The effectiveness of an agile software methodology: empirical evidence on humanistic aspects / Mazni Omar by Omar, Mazni

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