Kaggle is hosting an educational data mining competition: Kaggle Digit Recognizer, using MNIST data. Handwritten digit recognition is one of the few applications that kNN classifier performs well. Of course, the benchmark kNN classifier provided by the...
PDF available at here. Related post on KNN classification using SAS is here.In data mining and predictive modeling, it refers to a memory-based (or instance-based) algorithm for classification and regression problems. It is a widely used algorithm with...
Loss Given Default (LGD) is a key business metric of risk in financial service. One unique feature of this metric is overdispersion and the other is multi-mode. Finite mixture model is an effective way to accommodate both. Multi-mode refers to the case...
Recently, I am working on coding in SAS for a set of regularized regressions and need to compute trace of the projection matrix:$$ S=X(X'X + \lambda I)^{-1}X' $$.Wikipedia has a well written introduction to Trace @ here.To obtain the inverse of matrix ...
* Update: The SAS code and associated paper are now published at Journal of Statistical Software .========================================================================PROC GLIMMIX is good tool for generalized linear mixed model (GLMM), when the scal...
Low Rank Radial Smoothing using GLIMMIX [1], a semiparametric approach to smooth curves [2]. Specifying TYPE=RSMOOTH option in RANDOM statement, we can implement this spline smooth approach. The best thing is that for future scoring, data preparation i...
In the 2010 SASware Ballot®, a dedicated PROC for Randomized SVD was among the options. While an official SAS PROC will not be available in the immediate future as well as in older SAS releases, it is fairly simple to implement this algorithm using ex...
data nonlinear; do x=1 to 627; p=(sin(x/100)+1)*0.45; do j=1 to 100; x1=x+(j-1)/100; if ranuni(8655645)<=p then y=1; else y=0; output; drop p j; end; end; run; proc rank data=nonlinear out=nonlinearrank groups=...
K-Nearest-Neighbor, aka KNN, is a widely used data mining tool and is often called memory-based/case-based/instance-based method as no model is fit. A good introduction to KNN can be find at [1], or @ Wiki. Typically, KNN algorithm relies on a soph...
