Search Results - (( features generation mining algorithm ) OR ( java application learning algorithm ))

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. …”
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Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

“…The Particle Swarm Optimization algorithm is able to generate optimal values for the concrete features that maximizes the strength of concrete. …”
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Identifying significant features and data mining techniques in predicting cardiovascular disease / Mohammad Shafenoor Amin by Mohammad Shafenoor , Amin

“…Nonetheless, they have failed to generate an acceptable accuracy in prediction because of using wrong feature selection methods. …”
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

“…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). …”
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Discovering association rules for mining images datasets: a proposal by Hamzah, Azizi, O. K. Rahmat, Rahmita Wirza, Sulaiman, Md. Nasir

“…The algorithm has four major steps: feature extraction, object identification, auxiliary image creation and object mining. …”
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Enhanced ontology-based text classification algorithm for structurally organized documents by Oleiwi, Suha Sahib

“…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

“…A Binary Clonal Selection Algorithm is being proposed to ensure optimal generation of the superior final neuron states. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

“…The aim of this paper is to exploit the capability of bio-inspired search algorithms, together with wrapper and filtered methods in generating optimal set of features. …”
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Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

“…The data acquisition stage, data pre-processing, data annotation and feature extraction stage were designed and conducted in this paper to obtain and extract the EEG features from the Gameemo dataset. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Feature selection for financial data classification: Islamic finance application by Kartiwi, Mira, Gunawan, Teddy Surya, Arundina, Tika, Omar, Mohd. Azmi

“…Feature selection has been widely used in data preprocessing phase to improve the machine learning algorithm and model interpretability. …”
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Irrelevant feature and rule removal for structural associative classification by Mohd Shaharanee, Izwan Nizal, Jamil, Jastini

“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
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An enhanced intelligent database engine by neural network and data mining by Chua, Boon Lay, Khalid, Marzuki, Yusof, Rubiyah

“…An Intelligent Database Engine (IDE) is developed to solve any classification problem by providing two integrated features: decision-making by a backpropagation (BP) neural network (NN) and decision support by Apriori, a data mining (DM) algorithm. …”
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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Evolutionary-based feature construction with substitution for data summarization using DARA by Sia, Florence, Alfred, Rayner

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