Search Results - (( data visualization a algorithm ) OR ( variable learning based algorithm ))

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  1. 1

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…This process requires human labour to visually inspect and sort fruits, leading to variability and inefficiencies in the sorting process. …”
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    Article
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    Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

    Published 2021
    “…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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    Article
  3. 3

    Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

    Published 2017
    “…The activities were conducted involving first and fourth year undergraduate students and Master students in Programming 1 (31 students), Data Structure (6 students), Analysis of Algorithm (12 students) and Advanced Algorithm (22 students) courses respectively. …”
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    Conference or Workshop Item
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    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things by Ahmed Khan, Fazeel, Ibrahim, Adamu Abubakar

    Published 2023
    “…The next phase was deploying deep learning algorithms on a dataset having data generated from IIoT devices and sensors. …”
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  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
    “…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. 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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    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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    Thesis
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    Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest by Ghulam Hussain, Muhammad Thaqif, Shafeeq Lone, Aman, Maspo, Nur-Adib, Attarbashi, Zainab

    Published 2026
    “…This paper presents an unsupervised network-based anomaly detection framework that integrates deep autoencoders with the Isolation Forest algorithm. …”
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    Article
  9. 9

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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    Conference or Workshop Item
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    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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    Thesis
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    Budget visualizer using circle packing technique / Nursyahira Zulkeply by Zulkeply, Nursyahira

    Published 2019
    “…In order to construct this data visualization, the circle packing algorithm is used to visualize these budgets. …”
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    Thesis
  13. 13

    HAPTIC VISUALIZATION USING VISUAL TEXTURE INFORMATION by Adi, Waskito

    Published 2011
    “…A simple rendering algorithm, i.e. sine wave, produces a more stable force feedback, yet lacks surface details compared to the visual texture information approach.…”
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    Thesis
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    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. …”
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    Thesis
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    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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    Student Project
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    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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    Thesis
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    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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    Article
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