Hi, I am new to R and here is what I am doing in it now. I am using machine learning technique (svm) to do predictions. The data that I am using is one that is bound to grow perpetually. what I want to know is, say, I fed in a data set with 5000 data points to svm initially. The algorithm derives a certain intelligence (i.e.,output) based on these 5000 data points. I have an additional 10000 data points today. Now if i remove the first fed 5000 data and then feed in this new additional 10000 data, I want the algorithm to make use of the intelligence derived from the initial data(5000 data points) too while evaluating the new delta data points(10000) and the end result to be an aggregated measure of the total 15000 data. This is important to me from an efficiency point of view. If there are any other packages in r that does the same (i.e., enable statistical models to learn from the past experience continuously while deleting the prior data used from which the intelligence is derived) kindly post about them. This will be of immense help to me. Thanks in advance. divya -- View this message in context: http://r.789695.n4.nabble.com/Handling-ever-growing-data-in-svm-predictions-tp3795602p3795602.html Sent from the R help mailing list archive at Nabble.com.