Publications by John Mount
Coming up: principal components analysis
Just a “heads-up.” I’ve been editing a two-part series Nina Zumel is writing on some of the pitfalls of improperly applied principal components analysis/regression and how to avoid them (we are using the plural spelling as used in following Everitt The Cambridge Dictionary of Statistics). The series is looking absolutely fantastic and I th...
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For a short time: Half Off Some Manning Data Science Books
Our publisher Manning Publications is celebrating the release of a new data science in Python title Introducing Data Science by offering it and other Manning titles at half off until Wednesday, May 18. As part of the promotion you can also use the supplied discount code mlcielenlt for half off some R titles including R in Action, Second Edition ...
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Installing WVPlots and “knitting R markdown”
Some readers have been having a bit of trouble using devtools to install WVPlots. I thought I would write a note with a few instructions to help. These are things you should not have to do often, and things those of us already running R have stumbled through and forgotten about. First you will need install (likely admin) privileges on your mac...
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On ranger respect.unordered.factors
It is often said that “R it its packages.” One package of interest is ranger a fast parallel C++ implementation of random forest machine learning. Ranger is great package and at first glance appears to remove the “only 63 levels allowed for string/categorical variables” limit found in the Fortran randomForest package. Actually this appe...
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A demonstration of vtreat data preparation
This article is a demonstration the use of the R vtreat variable preparation package followed by caret controlled training. In previous writings we have gone to great lengths to document, explain and motivate vtreat. That necessarily gets long and unnecessarily feels complicated. In this example we are going to show what building a predictive mod...
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Using geom_step
geom_step is an interesting geom supplied by the R package ggplot2. It is an appropriate rendering option for financial market data and we will show how and why to use it in this article. Let’s take a simple example of plotting market data. In this case we are plotting the “ask price” (the publicly published price an item is available for ...
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Free e-book: Exploring Data Science
We are pleased to announce a new free e-book from Manning Publications: Exploring Data Science. Exploring Data Science is a collection of five chapters hand picked by John Mount and Nina Zumel, introducing you to various areas in data science and explaining which methodologies work best for each. Exploring Data Science gives you a free sample o...
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Why you should read Nina Zumel’s 3 part series on principal components analysis and regression
Short form: Win-Vector LLC’s Dr. Nina Zumel has a three part series on Principal Components Regression that we think is well worth your time. Part 1: the proper preparation of data (including scaling) and use of principal components analysis (particularly for supervised learning or regression). Part 2: the introduction of y-aware scaling to di...
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y-aware scaling in context
Nina Zumel introduced y-aware scaling in her recent article Principal Components Regression, Pt. 2: Y-Aware Methods. I really encourage you to read the article and add the technique to your repertoire. The method combines well with other methods and can drive better predictive modeling results. From feedback I am not sure everybody noticed that...
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vtreat version 0.5.26 released on CRAN
Win-Vector LLC, Nina Zumel and I are pleased to announce that ‘vtreat’ version 0.5.26 has been released on CRAN. ‘vtreat’ is a data.frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. (from the package documentation) ‘vtreat’ is an R package that incorporates a number of ...
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