Publications by Joel Cadwell
What Consumers Learn Before Deciding to Buy: Representation Learning
Features form the basis for much of our preference modeling. When asked to explain one’s preferences, features are typically accepted as appropriate reasons: this job paid more, that candidate supports tax reform, or it was closer to home. We believe that features must be the drivers since they so easily serve as rationales for past...
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Modeling Categories with Breadth and Depth
Religion is a categorical variable with followers differentiated by their degree of devotion. Liberals and conservatives check their respective boxes when surveyed, although moderates from each group sometimes seem more alike than their more extreme compatriots. All Smartphone users might be classified as belonging to the same segment...
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Recommending Recommender Systems When Preferences Are Not Driven By Simple Features
Why does lifting out a slice make the pizza appear more appealing?We can begin our discussion with the ultimate feature bundle – pizza toppings. Technically, a menu would only need to list all the toppings and allow the customers to build their own pizza. According to utility maximization, choice is a simple computation with the appeal of any p...
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Conjoint Analysis and the Strange World of All Possible Feature Combinations
The choice modeler looks over the adjacent display of cheeses and sees the joint marginal effects of the dimensions spanning the feature space: milk source, type, origin, moisture content, added mold or bacteria, aging, salting, packaging, price, and much more. Literally, if products are feature bundles, then one needs to specify all the sources ...
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Modeling the Latent Structure That Shapes Brand Learning
What is a brand? Metaphorically, the brand is the white sphere in the middle of this figure, that is, the ball surrounded by the radiating black cones. Of course, no ball has been drawn, just the conic thorns positioned so that we construct the sphere as an organizing structure (a form of reification in Gestalt psychology). Both perception and c...
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Clusters May Be Categorical but Cluster Membership Is Not All-or-None
Very early in the study of statistics and R, we learn that random variables can be either categorical or continuous. Regrettably, we are forced to relearn this distinction over and over again as we debug error messages produced by our code (e.g., “x must be numeric”). R will reminds us that if the function expects an argument to ...
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What Can We Learn from the Apps on Your Smartphone? Topic Modeling and Matrix Factorization
The website for The Burning House begins with a simple question:If your house was burning, what would you take with you? It’s a conflict between what’s practical, valuable and sentimental. What you would take reflects your interests, background and priorities. Think of it as an interview condensed into one question.But what about ...
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Centering and Standardizing: Don’t Confuse Your Rows with Your Columns
R uses the generic scale( ) function to center and standardize variables in the columns of data matrices. The argument center=TRUE subtracts the column mean from each score in that column, and the argument scale=TRUE divides by the column standard deviation (TRUE are the defaults for both arguments). For instance, weight and height come in differ...
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What is Data Science? Can Topic Modeling Help?
Predictive analytics often serves as an introduction to data science, but it may not be the best exemplar given its long history and origins in statistics. David Blei, on the other hand, struggles to define data science through his work on topic modeling and latent Dirichlet allocation. In Episode 10 of Talking Machines, Blei discusses his attem...
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Clusters Powerful Enough to Generate Their Own Subspaces
Cluster are groupings that have no external label. We start with entities described by a set of measurements but no rule for sorting them by type. Mixture modeling makes this point explicit with its equation showing how each measurement is an independent draw from one of K possible distributions.Each row of our data matrix contains th...
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