Example: XORΒΆ
The exclusive or (XOR) is a logical operation that outputs true when inputs differ.
import numpy as np
import pandas as pd
from lapart import train,test
xtrain = pd.read_csv('xor_train.csv').as_matrix()
xAtest = pd.read_csv('xor_test.csv').as_matrix()
xAtrain,xBtrain = xtrain[:,0:2],xtrain[:,2:3]
xAtrain
array([[ 0. , 0. ],
[ 1. , 0. ],
[ 0. , 1. ],
[ 1. , 1. ],
[ 1. , 1. ],
[ 0.9, 0.9],
[ 0.1, 0.8],
[ 0.2, 0.2],
[ 1. , 1. ]])
xBtrain
array([[ 0. ],
[ 1. ],
[ 1. ],
[ 0. ],
[ 0. ],
[ 0.1],
[ 0.8],
[ 0. ],
[ 0. ]])
xAtest
array([[ 0.1 , 0.9 ],
[ 1. , 0. ],
[ 0. , 0. ],
[ 1. , 1. ],
[ 0. , 1. ],
[ 0.15, 0.1 ]])
rA,rB = 0.8,0.8
TA,TB,L,t = train.lapArt_train(xAtrain,xBtrain,rhoA=rA,rhoB=rB,memory_folder='templates',update_templates=False)
C,T,Tn,df,t = test.lapArt_test(xAtest,rhoA=rA,rhoB=rB,memory_folder='templates')
C
array([[ 1.],
[ 1.],
[ 0.],
[ 0.],
[ 1.],
[ 0.]])