Non-Linear Classification Methods in Spark
In a previous post I covered how to apply classical linear estimators like support vector machines or logistic regression to a non-linear dataset using the kernel method. This article can …
Non-Linear Support Vector Machines (SVM)
1. Introduction Figure 1: The figure show three lines separating the black and the green group. This blog post is about Support Vector Machines (SVM), but not only about SVMs. …
Kernel Regression using Pyspark
1. Kernel Regression using Pyspark The red curve shows the true function m(x) while the green dots show the estimated curve evaluated using an random grid. The blue points are …
Nonparametric Density estimation using Spark
1. A Nonparametric Density implementation in Spark The red curve shows the true density while the blue dots show the estimated density evaluated using an equidistant grid. One of my …
Functional Regression with Spark
1. Functional Regression Let the covariate be an at least twice continuously differentiable random function defined wlog. on an interval and the corresponding the response. For simplicity we assume centered …
Functional Principal Component Analysis with Spark
1.) Functional Principal Component Analysis Let be a centered smooth random function in , with finite second moment . Without loss of generality we assume instead of some arbitrary compact …