Search Results - (( knowledge quality classification algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Hybrid genetic random forest algorithm for the identification of ISI-indexed articles / Mohammadreza Moohebat by Mohammadreza, Moohebat

“…This speed of knowledge growth highlights the role of scientific manuscripts in spreading this valuable knowledge around the world. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Thus, the challenge is how to develop an efficient model that can decrease the learning time without affecting the quality of the generated classification rules. Huge information systems or data sets usually have some missing values due to unavailable data that affect the quality of the generated classification rules. …”
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Comparing the knowledge quality in rough classifier and decision tree classifier by Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy

“…The experimental result shows that Rc and DTc own capability to generate quality knowledge since most of the results are comparable. …”
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IMPACT OF NUMBER OF ATTRIBUTES ON THE ACCURACY OF HUMAN MOTION CLASSIFICATION by Chan, Choon K, Girma, T. Chala*

“…The quality of the human motion data faces challenges in producing high classification accuracy in large data streams for essential knowledge discovery. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…However, numerous studies targeted at investigating several improved techniques of grading, and classification of the current oil palm maturity classification in order to enhance the oil palm yield in terms of quality, and quantity annually have been carried out. …”
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Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

“…Consequently, this proposed model could be extended for logic mining applications to tackle classification tasks. The optimized final neuron states will enhance the retrieval of high-quality induced logic, which is effective for classification and knowledge extraction.…”
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Graduates employment classification using data mining approach by Ab Aziz, Mohd Tajul Rizal, Yusof, Yuhanis

“…Data Mining is a platform to extract hidden knowledge in a collection of data.This study investigates the suitable classification model to classify graduates employment for one of the MARA Professional College (KPM) in Malaysia.The aim is to classify the graduates into either as employed, unemployed or further study.Five data mining algorithms offered in WEKA were used; Naïve Bayes, Logistic regression, Multilayer perceptron, k-nearest neighbor and Decision tree J48.Based on the obtained result, it is learned that the Logistic regression produces the highest classification accuracy which is at 92.5%. …”
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Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

“…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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Filter-wrapper based feature ranking technique for dynamic software quality attributes by Kamaruddin, Siti Sakira, Yahaya, Jamaiah, Deraman, Aziz, Ahmad, Ruzita

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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.] by Kasim, Nadia, Zainol Abidin, Siti Nazifah, Abu Mangshor, Nur Nabilah, Mohamed Hamzah, Hazwa Hanim, Abd Rahim, Nurul Zahirah

“…The ability to identify maturity stage of banana will be a great support but only experts can determine the maturity stage accurately. Lack of knowledge and skill of maintaining fruit quality standard to match the international standard is a problem faced by the farmers. …”
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Local threshold identification and gray level classification of butt joint welding imperfections using robot vision system by Mohd Shah, Hairol Nizam

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An improved genetic-fuzzy system for classification and data analysis by Lahsasna, A., Seng, W.C.

“…Interpretability of classification systems, which refers to the ability of these systems to express their behavior in an understandable way, has recently gained more attention and it is considered as an important requirement especially for knowledge-based systems. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…With closed itemset mining already being a preferred choice for complexity and redundancy reduction during rule generation, this study has further confirmed that overall closed itemset based association rules are also of better quality in terms of classification precision and recall, and precision and recall on individual class examples. …”
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On the training sample size and classification performance: An experimental evaluation in seismic facies classification by Babikir, I., Elsaadany, M., Sajid, M., Laudon, C.

“…Machine learning algorithms (MLAs) perform better when enough high-quality training data is provided. …”
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A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts by Nur Faiqah ‘Aqilah binti Fuaad