Search results for: svm regression
It would be nice if we can predict the future. For example, give the following time series, can we predict the next point? Let’s use SVM regression, which is said to be powerful. We use the immediate past data point as the predictor. We train o
One particular nice thing about SVR is that the weight of each feature reflects the feature’s true contribution. If some features are highly correlated (this is common in neuroimaging data – e.g. adjacent voxel activity are very similar),
SVM is mostly commonly used for binary classifications. But one branch of SVM, SVM regression or SVR, is able to fit a continuous function to data. This is particularly useful when the predicted variable is continuous. Here I tried some very simple c
updated: 2010/01/05, add plot of original data Assume our data contains two features and they are highly correlated (say, r>0.9). The 1st feature does slightly better than the 2nd one in classifying the data. The question is, is the weight of the
