Search Results - (( data verification mining algorithm ) OR ( code classification mining algorithm ))

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  1. 1
    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer

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

    Published 2017
    “…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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    Thesis
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  2. 2
    Comparative analysis for topic classification in juz Al-Baqarah

    Comparative analysis for topic classification in juz Al-Baqarah by Rahman, Mohamad Izzuddin, Samsudin, Noor Azah, Mustapha, Aida, Abdullahi Oyekunle, Adeleke

    Published 2018
    “…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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  3. 3
    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…Data mining analysis takes place in four stages: data pre-processing, data classification, classification of attributes by stages of CKD, and classification model verification using Microsoft Excel and Waikato Environmental for Knowledge Analysis (WEKA) version 3.8.5 software. …”
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  4. 4
    An enhanced intelligent database engine by neural network and data mining

    An enhanced intelligent database engine by neural network and data mining by Chua, Boon Lay, Khalid, Marzuki, Yusof, Rubiyah

    Published 2000
    “…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. Previous experimental results show the accuracy of NN (90%) and DM (60%) to be drastically distinct. …”
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  5. 5
    Classification of metamorphic virus using n-grams signatures

    Classification of metamorphic virus using n-grams signatures by A Hamid, Isredza Rahmi, Md Sani, Nur Sakinah, Abdullah, Zubaile, Mohd Foozy, Cik Feresa, Kipli, Kuryati

    Published 2020
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  6. 6
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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    Thesis
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  7. 7
    Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman

    Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

    Published 2016
    “…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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  8. 8
    A Hybrid Evaluation Metric for Optimizing Classifier

    A Hybrid Evaluation Metric for Optimizing Classifier by Hossin, M., Sulaiman, M.N, Mustapha, A., Mustapha, N., Rahmat, R.W

    Published 2011
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    Proceeding
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  9. 9
    A hybrid evaluation metric for optimizing classifier

    A hybrid evaluation metric for optimizing classifier by Hossin, Mohammad, Sulaiman, Md. Nasir, Mustapha, Aida, Mustapha, Norwati, O. K. Rahmat, Rahmita Wirza

    Published 2011
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  10. 10
    An enhanced android botnet detection approach using feature refinement

    An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

    Published 2019
    “…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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