for initit in range(args.numinit):
poisx,poisy = init(trainx,trainy,int(args.trainct*totprop/(1-totprop)+0.5))
clf, _ = genpoiser.learn_model(np.concatenate((trainx,poisx),axis=0),trainy+poisy,None)
err = genpoiser.computeError(clf)[0]
print("Validation Error:", err)
if err > besterr:
bestpoisx, bestpoisy, besterr = np.copy(poisx), poisy[:], err
poisx, poisy = np.matrix(bestpoisx), bestpoisy
poiser = types[args.model](trainx, trainy, testx, testy, validx, validy,\
args.eta, args.beta, args.sigma, args.epsilon,\
args.multiproc, trainfile, resfile,\
args.objective, args.optimizey, colmap)
Sir with respect, i have implemented your code but there raised an issue after visualisation was set to true for visualising the dataset i.e the global "colmap" is triggering error which state that it was not defined. I am unable to trace it where it be place. Please kindly share your suggestions.
With rgrd
Tiken