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Max Kuhn, Kjell Johnson
JLJ - Predict - if you will - your interest in this work by reading my notes below of quotes that I find interesting to me.
Although I downloaded the R project from the Internet I could not get any of the author's code to run - I kept getting error messages when I tried to install the various packages. The instructions for doing this were confusing and/or nonexistent when errors happened. Apparently it never occurred to the authors that a step-by-step procedure to download and execute the code (and updated over time) would be a worthwhile thing to do.
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vii This is a book on data analysis with a specific focus on the practice of predictive modeling. The term predictive modeling may stir associations such as machine learning, pattern recognition, and data mining... We intend this work to be a practicioner's guide to the predictive modeling process and a place where one can come to learn about the approach and to gain intuition about the many commonly used and modern, powerful models.
p.2 Predictive models now permeate our existence.
p.19 The first step in any model building process is to understand the data, which can most easily be done through a graph.
p.26 At some point in the process, a specific model must be chosen... At face value, model building appears straightforward: pick a modeling technique, plug in data, and generate a prediction. While this approach will generate a predictive model, it will most likely not generate a reliable, trustworthy model for predicting new samples. To get this type of model, we must first understand the data and the objective of the modeling. Upon understanding the data and objectives, we then pre-process and split the data. Only after these steps do we finally proceed to building, evaluating, and selecting models.
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