Large mean squared error in sklearn regressors
that's possibly due to poor parameter tuning. 
Try reducing C for SVR and increasing n_estimators for RFR. 

A nice approach is to gridsearch through the parameter, and plot the metric result. 

Another thing that might help is to normalize the parameters (sklearn.preprocessing.StandardScaler) and to remove the skew from the target (usually log transform or 1/target transform works better)