Search Results - (( _ valuation system algorithm ) OR ( label classification mining algorithm ))*

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  1. 1

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
    “…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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    Thesis
  2. 2

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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    Thesis
  3. 3

    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
    “…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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    Article
  4. 4

    Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

    Published 2021
    “…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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    Proceeding
  5. 5

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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    Thesis
  6. 6

    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
  7. 7

    Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

    Published 2024
    “…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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    Article
  8. 8

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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    Thesis
  9. 9

    A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

    Published 2023
    “…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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    Final Year Project / Dissertation / Thesis
  10. 10

    Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

    Published 2023
    “…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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    Thesis
  11. 11

    The adaptability of Industrial Revolution 4.0 technology in valuation field / Asmida Shafina Osman by Osman, Asmida Shafina

    Published 2023
    “…The study reveals that the majority of valuers have embraced IR4.0 technologies, finding them beneficial for simplifying work processes and making informed decisions. Drones and GIS systems have been utilized for property inspections and site analysis, while Al and ML algorithms have automated data analysis, leading to improved decision-making. …”
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    Thesis
  12. 12

    The adaptability of Industrial Revolution 4.0 in valuation field / Asmida Shafina Osman and Nor Azalina Yusnita Abdul Rahman by Osman, Asmida Shafina, Abdul Rahman, Nor Azalina Yusnita

    Published 2023
    “…The study reveals that the majority of valuers have embraced IR4.0 technologies, finding them beneficial for simplifying work processes and making informed decisions. Drones and GIS systems have been utilized for property inspections and site analysis, while AI and ML algorithms have automated data analysis, leading to improved decision-making. …”
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    Conference or Workshop Item
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    An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique by Hameed, Asaad Shakir

    Published 2021
    “…The valuate of performance HDDETS algorithm comparison to existing hybrid-based algorithms, namely: Biogeography-Based Optimization Tabu Search (BBOTS), Whale Algorithm with Tabu Search (WAITS), Hybrid Ant System (HAS), Lexisearch and Genetic Algorithms (LSGA), and Golden Ball Simulated Annealing (GBSA) algorithms. …”
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    Thesis
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  17. 17

    Adaptive Selection Of KLSE Stocks Using Neural Networks by Kok, Chee Foong

    Published 2002
    “…Hence in this study, neural network technology is deployed to build an adaptive neural net trading system, specifically adopting the multilayer feedforward network with backpropagation learning algorithm. …”
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    Thesis