Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography

2020 ◽  
pp. 1-1
Author(s):  
Lin Yin ◽  
Kun Wang ◽  
Tong Tong ◽  
Yu An ◽  
Hui Meng ◽  
...  
Keyword(s):  
Bayesian Learning ◽  
Nearest Neighbor ◽  
Sparse Bayesian Learning ◽  
Learning Method ◽  
K Nearest Neighbor ◽  
Bioluminescence Tomography ◽  
Tumor Morphology

scholarly journals Tropical Balls and Its Applications to K Nearest Neighbor over the Space of Phylogenetic Trees

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 779
Author(s):  
Ruriko Yoshida
Keyword(s):  
Supervised Learning ◽  
Phylogenetic Trees ◽  
Nearest Neighbor ◽  
Nearest Neighbors ◽  
High Dimensional ◽  
Learning Method ◽  
Dimensional Vector ◽  
K Nearest Neighbor ◽  
K Nearest Neighbors

A tropical ball is a ball defined by the tropical metric over the tropical projective torus. In this paper we show several properties of tropical balls over the tropical projective torus and also over the space of phylogenetic trees with a given set of leaf labels. Then we discuss its application to the K nearest neighbors (KNN) algorithm, a supervised learning method used to classify a high-dimensional vector into given categories by looking at a ball centered at the vector, which contains K vectors in the space.

scholarly journals Super-Resolution Ultrasound Imaging by Sparse Bayesian Learning Method

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 47197-47205
Author(s):  
Ying Liu ◽  
Yi Yang ◽  
Yuexia Shu ◽  
Tianyang Zhou ◽  
Jianwen Luo ◽  
...  
Keyword(s):  
Ultrasound Imaging ◽  
Bayesian Learning ◽  
Super Resolution ◽  
Sparse Bayesian Learning ◽  
Learning Method

scholarly journals Performance Analysis of KNN on Different Types of Attributes

2018 ◽  
Vol 7 (02) ◽  
pp. 23628-23631
Author(s):  
R.Nancy Beaulah
Keyword(s):  
Nearest Neighbor ◽  
Performance Comparison ◽  
Data Sets ◽  
Learning Method ◽  
K Nearest Neighbor ◽  
Instance Based Learning ◽  
Different Types ◽  
Classification Tasks ◽  
High Level ◽  
Learning Data

Data Mining is an inter-disciplinary promising field that focuses on access of information useful for high level decisions and also includes Machine Learning. Data Miners evaluate and filter the data as a result and convert the data into useful information. The useful information is converted into knowledge by performing some techniques. The K-Nearest Neighbor (K-NN) algorithm is an instance based learning method that has been widely used in many pattern classification tasks due to its simplicity, effectiveness and robustness. This paper presents a performance comparison of KNN algorithm in various data sets that includes different types of attributes. The results of this paper are achieved using WEKA tool.

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