Analysis of precision and accuracy in a simple model of machine learning

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2
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8

초록

Machine learning is a procedure where a model for the world is constructed from a training set of examples. It is important that the model should capture relevant features of the training set, and at the same time make correct prediction for examples not included in the training set. I consider the polynomial regression, the simplest method of learning, and analyze the accuracy and precision for different levels of the model complexity. © 2017, The Korean Physical Society.

키워드

Machine Learning; Regression; Inference Methods; DEEP NEURAL-NETWORKS; RECOGNITION; PREDICTION
제목
Analysis of precision and accuracy in a simple model of machine learning
저자
Lee, J.
DOI
10.3938/jkps.71.866
발행일
2017-12
유형
Article
저널명
Journal of the Korean Physical Society
권
71
호
12
페이지
866 ~ 870