Search Results - (( based optimization based algorithm ) OR ( quality classification mining algorithm ))

An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

“…First, the feature importance was evaluated using gain ratio algorithm, and the result was ranked, leading to selection of the optimal feature subset. …”
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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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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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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

“…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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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization by Chern-Tong, H., Aziz, I.A.

“…To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
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A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization by Chern-Tong, H., Aziz, I.A.

“…To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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Data mining approach to herbs classification by Ahmad Dali, Adillah Dayana, Omar, Nurul Aswa, Mustapha, Aida

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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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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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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Estimating 1-MCP application for Kampuchea guava with data mining technology by Ding, Phebe, Khor, Kor Chin

“…In this preliminary study, data mining (DM) technology was utilized to achieve fast estimation of 1-MCP application based on different qualities of 'Kampuchea' Guava. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

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Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The classification accuracy, the number of rules and the maximum length of rules obtained from the SIPIDRIP method was compared with other rough set method such as Genetic Algorithm (GA), Johnson, Holte l R, Dynamic and Exhaustive method. …”
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Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

“…This study employs a combination of data mining tasks, such as clustering and classification, to undertake the prediction task. …”
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Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Rough set discretization: Equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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