Abstract
Model evaluation is the most important step in developing any machine learning solution. At this stage in model development we measure the model performance and decide whether to go ahead with the model or revisit all our previous steps as described in the PEBE, our machine learning process flow, in Chapter 1. In many cases, we may even discard the complete model based on the performance metrics. This phase of the PEBE plays a very critical role in the success of any ML-based project.
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© 2019 Karthik Ramasubramanian and Abhishek Singh
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Ramasubramanian, K., Singh, A. (2019). Machine Learning Model Evaluation. In: Machine Learning Using R. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-4215-5_7
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DOI: https://doi.org/10.1007/978-1-4842-4215-5_7
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-4214-8
Online ISBN: 978-1-4842-4215-5
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