newGroup = currentGroup
else:
print("\t\t current R2 =\t %.10f" % currentR2)
print("\t\t best R2 =\t\t %.10f" % bestR2)
print("** updated group structure is: %s" % (newGroup.partition, ))
# if group structure is not empty, a new covariate can be added to an existing group
# print oldGroup.size
if oldGroup.size is not 0:
print "** Add to an existing group: **"
# can add new covariate to existing group
for covariateInd in covariatesPool:
for groupInd in np.arange(oldGroup.size)+1:
# print oldGroup.partition
print("\t try adding covariate %d " % covariateInd)
print("\t in group %d ..." % groupInd)
currentGroup = oldGroup.addNewCovariateToGroup(covariateInd, groupInd)
print("\t\t current group structure: %s " % (currentGroup.partition,))
# print currentGroup.partition
dataForOKGT, groupForOKGT = data.getGroupedData(currentGroup)
print groupForOKGT.partition
xkernels = [kernel] * groupForOKGT.size
parametersForOKGT = Parameters(groupForOKGT, ykernel, xkernels)
currentOKGT = OKGTReg(dataForOKGT, parametersForOKGT)
# res = currentOKGT.train_Vanilla()
res = currentOKGT.train_Nystroem(10)
currentR2 = res['r2']
if currentR2 > bestR2:
print("\t\t current R2 =\t %.10f \t *" % currentR2)
bestR2 = currentR2
bestOKGT = currentOKGT
bestCovariateIndex = covariateInd
