Search Results - (( data extraction method algorithm ) OR ( variable generation using algorithm ))

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    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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    Thesis
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    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2017
    “…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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    Article
  4. 4

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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    Thesis
  5. 5

    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

    Published 2024
    “…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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    Article
  6. 6

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…Furthermore, to confirm the performances of the proposed multi-sensor fusion methods using challenging motion sensor data generated using smartphones and wearable sensors. …”
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    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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    Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

    Published 2018
    “…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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    Article
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    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

    Published 2016
    “…The result of this research show that nearly all image has accuracy more than 80% that prove that K-Means clustering algorithm are suitable as method for extracting meaningful information in images.…”
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    Thesis
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    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. …”
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    Thesis
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    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are a lot of feature extraction methods and classification methods for iris classification. …”
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    Monograph
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    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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    Message based random variable length key encryption algorithm. by Mirvaziri, Hamid, Jumari, Kasmiran, Ismail, Mahamod, Mohd Hanapi, Zurina

    Published 2009
    “…Value of random number should be greater than 35 bits and plaintext must be at least 7 bits. A padding algorithm was used for small size messages or big random numbers. …”
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    A fast feature extraction algorithm for image and video processing by Abdulhussain, Sadiq H., Ramli, Abdul Rahman, Mahmmod, Basheera M., Saripan, M. Iqbal, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Baker, Thar, Flayyih, Wameedh Nazar, Jassim, Wissam A.

    Published 2019
    “…We compared the proposed method with the traditional approach of feature extraction using a standard image technique. …”
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    Conference or Workshop Item
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    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

    Published 2020
    “…In the training phase, around 22% of the 110,057 beats data extracted from 48 records were utilized. Using only these 22% labeled training data, our proposed algorithm was able to classify the remaining 78% of the database into 16 classes. …”
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