Supervised Learning: Model Popularity from Past to Present

Since data scraping from Google Scholar is notoriously hard, I relied on helpful advice from ScrapeHero to gather the data.I included the following 13 supervised approaches in the analysis: neural networks, deep learning, SVMs, random forests, decision trees, linear regression, logistic regression, Poisson regression, ridge regression, lasso regression, k-nearest neighbors, linear discriminant analysis, and log-linear models..Note that for lasso regression, the terms lasso regression and lasso model were considered..For nearest neighbors, the terms k-nearest neighbor and k-nearest neighbour were considered..The resulting data set indicates the number of publications associated with each supervised model from 1950 until now.To analyze the longitudinal data, I will differentiate two periods: the early days of machine learning (1950 to 1980), in which few models were available, and the formative years (1980 until now), in which interest in machine learning surged and many new models were developed..Note that in the following visualizations only the most relevant methods are shown.As we can see from Figure 1, linear regression was the dominating method between 1950 and 1980..In comparison, other machine learning models were mentioned extremely rarely in the scientific literature..Starting from the 1960s, however, we can see that the popularity of neural networks and decision trees began to grow..We can also see that logistic regression was not widely available yet, with only slight increases in the number of mentions at the end of the 1970s.Figure 2 demonstrates that the supervised models that were mentioned in scientific publications became considerably more diverse starting from the late 1980s..Importantly, the rate at which machine learning models were mentioned in the scientific literature has steadily increased until 2013..The plot particularly demonstrates the popularity of linear regression, logistic regression, and neural networks..As we have seen before, linear regression has already been popular way before 1980..In 1980, however, the popularity of neural networks and logistic regression started growing rapidly.. More details

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