Results 211 to 220 of about 50,437 (269)
Simultaneous Assessment of Chicken Freshness and Authenticity Using a Single Multispectral Imaging Device: A Cross-Laboratory Evaluation Using Identical Instruments. [PDF]
Sensors (Basel)Lytou A +4 more
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Prediction Pipeline Selection for Incomplete Clinical Data via Missingness Fingerprints and Instance Augmentation. [PDF]
Bioengineering (Basel)Li R, Shen Z, Wu C, Li J, Tian Y.
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Dynamic monitoring of salicylic acid and vitamin B<sub>2</sub> during the apple boiling process based on fluorescence spectroscopy and machine learning. [PDF]
Food Chem XXu H +10 more
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Handcrafted Versus Deep Feature Extraction Methods for MRI-Based Multiple Sclerosis Diagnosis. [PDF]
Diagnostics (Basel)Yahia S, Bouchrika T, Bouchelligua W.
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Fundamenta Informaticae, 2021
The k Nearest Neighbor (KNN) algorithm has been widely applied in various supervised learning tasks due to its simplicity and effectiveness. However, the quality of KNN decision making is directly affected by the quality of the neighborhoods in the modeling space.
Linh Le +2 more
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The k Nearest Neighbor (KNN) algorithm has been widely applied in various supervised learning tasks due to its simplicity and effectiveness. However, the quality of KNN decision making is directly affected by the quality of the neighborhoods in the modeling space.
Linh Le +2 more
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kNN-P: A kNN classifier optimized by P systems
Theoretical Computer Science, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Juan Hu +3 more
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An Improved kNN Algorithm – Fuzzy kNN
2005As a simple, effective and nonparametric classification method, kNN algorithm is widely used in text classification. However, there is an obvious problem: when the density of training data is uneven it may decrease the precision of classification if we only consider the sequence of first k nearest neighbors but do not consider the differences of ...
Wenqian Shang +5 more
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Proceedings of the 4th International Conference on Communication and Information Processing, 2018
K nearest neighbor (kNN) method is a popular classification method in data mining because of its simple implementation and significant classification performance. However, kNN do not scale well to big datasets. In this paper, CLUKER, a novel kNN regression method based on hierarchical clustering, is proposed.
Yi Xiang +3 more
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K nearest neighbor (kNN) method is a popular classification method in data mining because of its simple implementation and significant classification performance. However, kNN do not scale well to big datasets. In this paper, CLUKER, a novel kNN regression method based on hierarchical clustering, is proposed.
Yi Xiang +3 more
openaire +1 more source
Proceedings of the 2008 ACM conference on Recommender systems, 2008
Recommender systems, based on collaborative filtering, draw their strength from techniques that manipulate a set of user-rating profiles in order to compute predicted ratings of unrated items. There are a wide range of techniques that can be applied to this problem; however, the k-nearest neighbour (kNN) algorithm has become the dominant method used in
Neal Lathia, Stephen Hailes, Licia Capra
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Recommender systems, based on collaborative filtering, draw their strength from techniques that manipulate a set of user-rating profiles in order to compute predicted ratings of unrated items. There are a wide range of techniques that can be applied to this problem; however, the k-nearest neighbour (kNN) algorithm has become the dominant method used in
Neal Lathia, Stephen Hailes, Licia Capra
openaire +1 more source