Which classification algorithms can handle 24000 features? What are their pros and cons?
Deep Learning Algorithms and Graphical model algorithms can handle that scale of features.
For example a typical parsing algorithm using CRF++ computes millions of features. In case of Deep Learning, A typical image of 256*256*3 has to deal with 196608 number of features where each pixel in image is a feature.