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What is Training Dataset

Handbook of Research on Interdisciplinary Perspectives on the Threats and Impacts of Pandemics
The dataset used to train the algorithm.
Published in Chapter:
Comparison of Machine Learning Algorithms in Predicting the COVID-19 Outbreak
Asiye Bilgili (Halic University, Turkey)
DOI: 10.4018/978-1-7998-8674-7.ch017
Abstract
Health informatics is an interdisciplinary field in the computer and health sciences. Health informatics, which enables the effective use of medical information, has the potential to reduce both the cost and the burden of healthcare workers during the pandemic process. Using the machine learning algorithms support vector machines, naive bayes, k-nearest neighbor, and C4.5 algorithms, a model performance evaluation was performed to identify the algorithm that will show the highest performance for the prediction of the disease. Three separate training and test datasets were created 70% - 30%, 75% - 25%, and 80% - 20%, respectively. The implementation phase of the study was carried out by following the CRISP-DM steps, and the analyses were made using the R language. By examining the model performance evaluation criteria, the findings show that the C4.5 algorithm showed the best performance with 70% training dataset.
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Motion Planning Method for In-Pipe Walking Robots Using Height Maps and CNN-Based Pipe Branches Detector
A set of labeled samples used by on optimizer algorithm to update the weights of a neural network, so as to enable it to better predict correct labels, given the samples.
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