深度学习
人工智能
心理信息
计算机科学
机器学习
卷积神经网络
人工神经网络
循环神经网络
梅德林
政治学
法学
作者
Christopher J. Urban,Kathleen M. Gates
出处
期刊:Psychological Methods
[American Psychological Association]
日期:2021-04-01
卷期号:26 (6): 743-773
被引量:39
摘要
Deep learning has revolutionized predictive modeling in topics such as computer vision and natural language processing but is not commonly applied to psychological data. In an effort to bring the benefits of deep learning to psychologists, we provide an overview of deep learning for researchers who have a working knowledge of linear regression. We first discuss several benefits of the deep learning approach to predictive modeling. We then present three basic deep learning models that generalize linear regression: the feedforward neural network (FNN), the recurrent neural network (RNN), and the convolutional neural network (CNN). We include concrete toy examples with R code to demonstrate how each model may be applied to answer prediction-focused research questions using common data types collected by psychologists. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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