self.old_objective_value = -(sys.maxint-1)
self.logfh = logfh
+ self.old_w = cb.matrix([0.0] ,(1,1))
+
#self.P.tofile(open('matrix_P_%d_%d'%(self.P.size[0],self.P.size[1]),'w+'))
#self.q.tofile(open('matrix_q_%d_%d'%(self.q.size[0],self.q.size[1]),'w+'))
#self.G.tofile(open('matrix_G_%d_%d'%(self.G.size[0],self.G.size[1]),'w+'))
if loss < self.EPSILON:
return False
- if self.old_w != None:
+ if self.old_w.size != (1,1):
scalar_prod = energy_deltas * self.old_w[0:self.numFeatures,0]
old_slack = self.old_w[self.numFeatures+idx,0]
if useMarginRescaling: