Search Results - lazy supervised algorithm

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  1. 1

    Companion: A Social Support Generating Application for Lonely and Socially Isolated Individuals using Lazy Supervised Algorithm by Buctuanon, Marisa, Comabig, Xavier, Mayola, Wavina Vivienne

    ISSN: 2423-1398, 2408-3755
    Published: Center for Policy, Research and Development Studies 30.06.2020
    “…-being. Thus, this study develops Companion, an app that utilizes the KNN algorithm to create a social support group that matches a seeker to the group based on his interest and problem at hand. He finds new friends with whom he can feel a sense of care, love, understanding, and belongingness. It comes with a set of physical activities designed for the group. The algorithm yields an 84% accuracy rate after evaluating the result…”
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    Journal Article
  2. 2

    Investigating the Impact of Min-Max Data Normalization on the Regression Performance of K-Nearest Neighbor with Different Similarity Measurements by Muhammad Ali, Peshawa J.

    ISSN: 2410-9355, 2307-549X
    Published: Koya University 30.06.2022
    Published in ARO (Koya) (30.06.2022)
    “… K-nearest neighbor (KNN) is a lazy supervised learning algorithm, which depends on computing the similarity between the target and the closest neighbor…”
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    Journal Article
  3. 3

    Batched Lazy Decision Trees by Guillame-Bert, Mathieu, Dubrawski, Artur

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 08.03.2016
    Published in arXiv.org (08.03.2016)
    “…We introduce a batched lazy algorithm for supervised classification using decision trees…”
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    Paper
  4. 4

    Comparison of Machine Learning Land Use-Land Cover Supervised Classifiers Performance on Satellite Imagery Sentinel 2 using Lazy Predict Library by Muhamad Iqbal Januadi Putra, Vincent Alexander

    ISSN: 2715-9930, 2715-9930
    Published: 01.01.2024
    Published in Indonesian Journal of Data and Science (01.01.2024)
    “…The utilisation of various supervised classifier algorithms in classifying land use and land cover (LULC…”
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    Journal Article
  5. 5

    A Novel Density-Based KNN in Pattern Recognition by Klidbary, Sajad Haghzad, Arabameri, Abazar

    ISSN: 2643-279X
    Published: IEEE 01.11.2023
    “…The k-nearest neighbor learning algorithm is indeed one of the most commonly used supervised algorithms in machine learning…”
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    Conference Proceeding
  6. 6

    Lazy texture selection based on active learning by Xia, Tian, Wu, Qing, Chen, Chun, Yu, Yizhou

    ISSN: 0178-2789, 1432-2315
    Published: Berlin/Heidelberg Springer-Verlag 01.03.2010
    Published in The Visual computer (01.03.2010)
    “… An active learning algorithm uses these labeled data to obtain an initial classifier and iteratively improves it until its performance becomes satisfactory…”
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    Journal Article
  7. 7

    ATSO: Asynchronous Teacher-Student Optimization for Semi-Supervised Image Segmentation by Huo, Xinyue, Xie, Lingxi, He, Jianzhong, Yang, Zijie, Zhou, Wengang, Li, Houqiang, Tian, Qi

    ISSN: 1063-6919
    Published: IEEE 01.06.2021
    “…Semi-supervised learning is a useful tool for image segmentation, mainly due to its ability in extracting knowledge from unlabeled data to assist learning from labeled data…”
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    Conference Proceeding
  8. 8

    An adaptive framework based on multi-model data fusion for one-day-ahead wind power forecasting by Vaccaro, A., Mercogliano, P., Schiano, P., Villacci, D.

    ISSN: 0378-7796, 1873-2046
    Published: Amsterdam Elsevier B.V 01.03.2011
    Published in Electric power systems research (01.03.2011)
    “… The latter is based on a local learning algorithm, called the Lazy Learning (LL) algorithm. This algorithm is sequentially updated, in order to adapt the whole architecture…”
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    Journal Article
  9. 9

    A Comparative Study of Supervised Machine Learning Techniques for Spam E-mail Filtering by Panigrahi, P. K.

    ISBN: 9781467329811, 1467329819
    Published: IEEE 01.11.2012
    “… of supervised machine learning techniques such as Bayes algorithms, lazy algorithms, tree algorithms, neural network…”
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    Conference Proceeding
  10. 10

    Integration of PSO-based advanced supervised learning techniques for classification data mining to predict heart failure by Mesran, Kmurawak, Remuz Mb, Windarto, Agus Perdana

    ISSN: 1693-6930, 2302-9293
    Published: Yogyakarta Ahmad Dahlan University 01.02.2024
    Published in Telkomnika (01.02.2024)
    “… This study proposes a novel approach for HF classification by integrating advanced supervised learning (ASL…”
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    Journal Article
  11. 11

    Ensemble of Supervised and Unsupervised Learning Models to Predict a Profitable Business Decision by Heidari, Maryam, Zad, Samira, Rafatirad, Setareh

    Published: IEEE 21.04.2021
    “… In this paper, we carry out a comprehensive analysis and study of seven machine learning algorithms for rent prediction, including Linear Regression, Multilayer Perceptron, Random Forest, KNN…”
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    Conference Proceeding
  12. 12

    Performance Assessment of Supervised Classifiers for Designing Intrusion Detection Systems: A Comprehensive Review and Recommendations for Future Research by Panigrahi, Ranjit, Borah, Samarjeet, Bhoi, Akash Kumar, Ijaz, Muhammad Fazal, Pramanik, Moumita, Jhaveri, Rutvij H., Chowdhary, Chiranji Lal

    ISSN: 2227-7390, 2227-7390
    Published: MDPI AG 01.03.2021
    Published in Mathematics (Basel) (01.03.2021)
    “… Numerous algorithms have been designed to address such complex application domains. Despite an enormous array of supervised classifiers, researchers are yet…”
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    Journal Article
  13. 13

    Real Time Lung Cancer Prediction Using Lazy Learning Technique by Jaswanth, K. Gowri, Adithya, P. Pavan, Eekshith, G. Sai, Hariharan, Shanmugasundaram, Kukreja, Vinay, Geetha, Dadala

    Published: IEEE 27.12.2024
    “… This study utilizes supervised machine learning algorithms, including Support Vector Machine (SVM…”
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    Conference Proceeding
  14. 14

    K Nearest Neighbor Based Model for Intrusion Detection System by Nikhitha, M., Jabbar, Dr.M.A.

    ISSN: 2277-3878, 2277-3878
    Published: 30.07.2019
    “… KNN is a supervised and lazy machine learning classifier, it shows its best performance in terms of accuracy and classifications…”
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    Journal Article
  15. 15

    Infinite Lattice Learner: an ensemble for incremental learning by Lovinger, Justin, Valova, Iren

    ISSN: 1432-7643, 1433-7479
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2020
    Published in Soft computing (Berlin, Germany) (01.05.2020)
    “…The state of the art in supervised learning has developed effective models for learning, generalizing, recognizing faces and images, time series prediction…”
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    Journal Article
  16. 16

    Comparison between Nearest Neighbours and Bayesian Network for demand forecasting in supply chain management by Gaur, Manas, Goel, Shruti, Jain, Eshaan

    ISBN: 9380544154, 9789380544151
    Published: Bharati Vidyapeeth, New Delhi 01.03.2015
    “…Machine Learning has found to be playing a significant role in solving issue of demand forecasting in supply chain management, where many traditional methods…”
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    Conference Proceeding
  17. 17

    A Lazy Ensemble Learning Method to Classification by Homayouni, Haleh, Hashemi, Sattar, Hamzeh, Ali

    ISSN: 1694-0814, 1694-0784
    Published: Mahebourg International Journal of Computer Science Issues (IJCSI) 01.09.2010
    “…Depending on how a learner reacts to the test instances, supervised learning divided into eager learning and lazy learning…”
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    Journal Article
  18. 18

    Coding schemes in neural networks learning classification tasks by van Meegen, Alexander, Sompolinsky, Haim

    ISSN: 2041-1723, 2041-1723
    Published: London Nature Publishing Group UK 09.04.2025
    Published in Nature communications (09.04.2025)
    “… Indeed, with appropriate scaling, supervised learning in neural networks can result in strong, task-dependent feature learning…”
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    Journal Article
  19. 19

    Chinese question Classification using Multilevel Random Walk by Kepei Zhang, Jieyu Zhao

    ISBN: 9781424465828, 1424465826
    Published: IEEE 01.10.2010
    “…Question classification is crucial for the automatically question answering. And Random Walk is a promising approach for semi-supervised learning problems of learning from labeled and unlabeled data…”
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    Conference Proceeding
  20. 20

    Certainty-Enhanced Active Learning for Improving Imbalanced Data Classification by Jui Hsi Fu, Sing Ling Lee

    ISBN: 1467300055, 9781467300056
    ISSN: 2375-9232
    Published: IEEE 01.12.2011
    “…In active learning algorithms, informative samples are usually queried for true labels according to the disagreement of existing hypotheses…”
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    Conference Proceeding