Search Results - (( java implementation bat algorithm ) OR ( program classification cell algorithm ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri by Masri, Nor Khirda

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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms by Wan Azani Mustafa, Khalis Khiruddin, Khairur Rijal Jamaludin, Firdaus Yuslan Khusairi, Shahrina Ismail

EMG signal classification for human computer interaction: a review by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…This review paper is to discuss the various methodologies and algorithms used for EMG signal classification for the purpose of interpreting the EMG signal into computer command.…”
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Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

“…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. …”
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Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification by Azzoni, Livio, Foulkes, Andrea S., Liu, Yan, Johnson, Margaret, Smith, Collette, Kamarulzaman, Adeeba, Montaner, Julio, Mounzer, Karam, Saag, Michael, Cahn, Pedro, Cesar, Carina, Krolewiecki, Alejandro, Sanne, Ian, Montaner, Luis J.

“…Methods and Findings: Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/ml). …”
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