Suppose I have an experiment where I have 70 features and 48 samples. The target variable is binary (0,1) and the 48 samples are divided such that 24 of them correspond to outcome 1 and the other 24 correspond to outcome 0.
Note that the data I have is an averaged data. In other words, each of the 48 samples is a result of "n" averaged trials.
I am interested in using SVM and obtaining the weight vector (70x1). In a way, I have less number of samples vs features. However, the data which I have is an outcome of averaged trials.
In case I don't have access to the raw data, what is the best way to deal with the data? And does having the mean of trials as my data give a privilege over having 48 raw-trails instead?