Package Updates
Several updates. All packages are on CRAN, but please use GitHub for the latest.
Mad (Data) Scientist
Musings, useful code etc. on R and data science
Latest posts
New qeML Plotting Function
I ve added a new function to qeML 1.2, qeMittalGraph, based on an idea by my student Aditya Mittal. Below is an example that I think is rather compelling. The basic idea is quite simple (and not necessarily new, just something I had not seen below): Instead of comparing several curves directly, plot their growth from Continue reading New qeML Plotting Function
New R Package: Data Science Looks at Discrimination (dsld)
I m very pleased to announce a new package, dsld, available on CRAN. This is the work of eight talented undergrad students. I provided the concept and some general guidance, but this is their work. The package is aimed at dealing with discrimination race, gender, age in the workplace, education, health care and so Continue reading New R Package: Data Science Looks at Discrimination (dsld)
New Paper on Data Privacy
Readers who are interested in the Data Privacy field may find our new paper (Perry, Matloff, Tendick) of interest, https://tdp.cat/issues21/tdp.a478a22.pdf…. There we introduce a new method that we call RWN, Randomization within Neighborhoods. We present a bit of supporting theory and do some empirical evaluation. We also present a qualitative comparison to other major methods, Continue reading…
Knowing Something vs. Knowing the Name of Something: Some Points about Causal Analysis
The famed physicist Richard Feynman once said, I learned very early the difference between knowing the name of something and knowing something, a lesson from his father. I think too often we in the statistics/machine learning field are guilty of only knowing the name of something. Well, in most cases, we may know a bit Continue reading Knowing Something vs. Knowing the Name of Something: Some…
Torch for R Now in the qeML Package
I ve added a new function, qeNeuralTorch, to the qeML package, as an alternative to the package s qeNeural. It is experimental as this point, but usable and I urge everyone to try it out. In this post, I will (a) state why I felt it desirable to add such a function, (b) show a couple of Continue reading Torch for R Now in the qeML Package
Quantile Regression with Random Forests
In my December 22 blog, I first introduced the classic parametric quantile regression (QR) concept. I then showed how one could use the qeML package to perform quantile regression nonparametrically, using the package s qeKNN function for a k-Nearest Neighbors approach. A reader then asked if this could be applied to random forests (RFs). The answer is yes, Continue reading Quantile Regression with…
qeML Example: Nonparametric Quantile Regression
In this post, I will first introduce the concept of quantile regression (QR), a powerful technique that is rarely taught in stat courses. I ll give an example from the quantreg package, and then will show how qeML can be used to do model-free QR estimation. Along the way, I will also illustrate the use of Continue reading qeML Example: Nonparametric Quantile Regression
A Comparison of Several qeML Predictive Methods
Is machine learning overrated, with traditional methods being underrated these days? Yes, ML has had some celebrated successes, but these have come after huge amounts of effort, and it s possible that similar effort with traditional methods may have produced similar results. A related issue concerns the type of data. Hard core MLers tend to divide Continue reading A Comparison of Several qeML…
data.table User Survey
The data.table 2023 user community survey is here, open until December 1st.