Random commentary about Machine Learning, BigData, Spark, Deep Learning, C++, STL, Boost, Perl, Python, Algorithms, Problem Solving and Web Search
Sunday, January 24, 2010
PCA is a dimension reduction technique for linearly separeted data. In order to deal with data that cannot be linearly separated, one can adopt the kernel trick. This generates the so called Kernel-PCA.