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What is KNN

Machine Learning for Societal Improvement, Modernization, and Progress
- K-nearest neighbors
Published in Chapter:
Machine Learning for Ecological Sustainability: An Overview of Carbon Footprint Mitigation Strategies
Vishnu S. Pendyala (San Jose State University, USA) and Saritha Podali (San Jose State University, USA)
DOI: 10.4018/978-1-6684-4045-2.ch001
Abstract
Among the most pressing issues in the world today is the impact of globalization and energy consumption on the environment. Despite the growing regulatory framework to prevent ecological degradation, sustainability continues to be a problem. Machine learning can help with the transition toward a net-zero carbon society. Substantial work has been done in this direction. Changing electrical systems, transportation, buildings, industry, and land use are all necessary to reduce greenhouse gas emissions. Considering the carbon footprint aspect of sustainability, this chapter provides a detailed overview of how machine learning can be applied to forge a path to ecological sustainability in each of these areas. The chapter highlights how various machine learning algorithms are used to increase the use of renewable energy, efficient transportation, and waste management systems to reduce the carbon footprint. The authors summarize the findings from the current research literature and conclude by providing a few future directions.
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Application of Machine Learning In Forensic Science
KNN is the distance-based algorithm K-nearest neighbor.
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Analysis of Different Image Processing Techniques for Classification and Detection of Cancer Cells
K nearest neighbors is a classification algorithm that classifies the object based on k nearest neighbors.
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Classification Algorithms and Control-Flow Implementation
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Holistic View on Detecting DDoS Attacks Using Machine Learning
K-Nearest Neighbours. Supervised method used for classification and regression problems, that attempts to determine what group a data point is in by looking at the data points around it.
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Automated Image Analysis Approaches in Histopathology
K - Nearest Neighbour. A classifier that decides on the class of an unlabeled sample based on its k nearest labeled neighbouring samples according to some distance measure (usually Euclidian).
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Machine Automation Making Cyber-Policy Violator More Resilient: A Proportionate Study
K-nearest neighbors the only outfit scheme of machine automation for the process of reversion and sorting insufficiencies. It itself uses the data of its scheme and come up with a newer feature set of facts basing on the actions of resemblance. Finally, sorting will be done through majority votes of its neighbors.
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