22 results for “K Nearest Neighbor (KNN)”

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Research ArticleOpen accessIn the keywordsBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,610 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsDiscrete Wavelet Transform Based Classification of Human Emotions Using Electroencephalogram SignalsMohamed RizonProblem statement: The aim of this study was to report the human emotion assessment using Electroencephalogram (EEG). Approach: An audio-visual induction based protocol was designed for inducing five different emotions (happy, surprise, fear, disgust and neutral) on 20 subjects in the age group of 19~39 years. EEG signals are recorded from 64 channels placed over entire scalp according to International … …American Journal of Applied Sciences, Vol. 7, Issue 7 · 31 Jul 2010 · 7,549 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPrincipal Component Analysis Based Feature Extraction, Morphological Edge Detection and Localization for Fast Iris RecognitionM. Suganthy, P. RamamoorthyThis study involves the Iris Localization based on morphological or set theory which is well in shape detection. Principal Component Analysis (PCA) is used for preprocessing, in which the removal of redundant and unwanted data is done. Applications such as Median Filtering and Adaptive thresholding are used for handling the variations in lighting and noise. Features are extracted using Wavelet … …Journal of Computer Science, Vol. 8, Issue 9 · 9 Aug 2012 · 7,748 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPredicting Missing Attribute Values Using k-Means ClusteringNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Predicting the value for missing attributes is an important data preprocessing problem in data mining and knowledge discovery tasks. Several methods have been proposed to treat missing data and the one used more frequently is deleting instances containing at least one missing value of a feature. When the dataset has minimum number of missing attribute values then we … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,873 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 622 accessesView PDF Cite

Research ArticleOpen accessIn the abstractOptimized Feature Selection for Kidney Ultrasound Image Classification Using Binary Coati Weighted Mean Vector AlgorithmFizhan Kausar, Ramamurthy B.The analysis of medical images presents many challenges, especially when making precise diagnoses. In pediatric Chronic Kidney Disease (CKD), early identification is critical because of its gradual progression to significant kidney failure. This study proposes a diagnostic framework for pediatric ultrasound image classification that incorporated machine learning and advanced feature selection methods. This approach is divided into four stages: Preprocessing, … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,563 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,900 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCrop Yield Prediction in Niger Using Machine Learning TechniquesMahaman Lawali Inoussa Garba, Naroua Harouna, Chaibou Kadri et al.Agriculture is the most impactful sector on Niger's economic growth. Stresses related to climate change and the environment are leading to a continuous decline in crop yield. Accurate crop yield forecasting is of paramount importance for farmers, government, policy makers, and other stakeholders to make most appropriate decisions regarding resource allocation and food security. This study examines the power of … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 5,792 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,653 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDF Cite