Search Results - evolution ((classification technique) OR (((computing techniques) OR (mining techniques))))

A review of homogenous ensemble methods on the classification of breast cancer data by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Data mining is a concept established by computer scientists to lead a secure and reliable classification and deduction of data. …”
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A review of homogenous ensemble methods on the classification of breast cancer data by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Data mining is a concept established by computer scientists to lead a secure and reliable classification and deduction of data. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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Data mining in computer auditing / Hiromi Wong, Siew Lan and Valery Fred Lee by Hiromi , Wong, Siew , Lan, Valery, Fred Lee

“…The report will cover the literature review that started with an introduction to computer auditing, introduction to data mining, data mining techniques (classification, neural network and sequential analysis), and the existing data mining software. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…The evolution of authoritative immunofingerprint mining technology is exerting a growing influence on comprehensive cancer diagnosis biology. …”
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Stacking with recursive feature elimination-isolation forest for classification of diabetes mellitus by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Izham, Mohd Jaya, Ashraf Osman, Ibrahim, Abulfaraj, Anas W., Binzagr, Faisal

“…Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. …”
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Stacking with recursive feature elimination-isolation forest for classification of diabetes mellitus by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Izham, Mohd Jaya, Ashraf Osman, Ibrahim, Abulfaraj, Anas W., Binzagr, Faisal

“…Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. …”
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Overview and future opportunities of sentiment analysis approaches for big data by Mohd Sharef, Nurfadhlina, Mat Zin, Harnani, Nadali, Samaneh

“…The contribution of this paper is two-fold: (i) this study reviews the state of the art of SA approaches. including sentiment polarity detection, SA features (explicit and implicit), sentiment classification techniques and applications of SA and (ii) this study reviews the suitability of SA approaches for application in the big data frameworks, as well as highlights the gaps and suggests future works that should be explored. …”
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Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Results show that the best feature selection is term frequency and trimming of the feature with a frequency greater than 95%. The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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Object detection and classification using few-shot learning in smart agriculture: A scoping mini review by Nitiyaa Ragu, Jason Teo

“…Its evolution over the previous two decades can be seen as the pinnacle of computer vision advancement. …”
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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

“…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

“…In evolution and ubiquitous computing systems, accelerometer-based human activity recognition has huge potential in a large number of application domains. …”

Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Multi-tier classification based on sentiment, type, emotion and purpose for online diabetes community / Wandeep Kaur Ratan Singh by Wandeep Kaur , Ratan Singh

“…The proposed framework was able to improve overall classification accuracy within each of its tiers and using a multi-tier framework, it was able to remove posts that do not contribute towards classification within the upper layers thus contributing to a more refined dataset for classification within its lower tiers. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

“…Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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A joint learning classification for intent detection and slot filling from classical to deep learning: a review by Muhammad Yusuf, Idris, Naomie, Salim, Anazida, Zainal, Sinarwati, Mohamad Suhaili

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