def get_ConfMatrix(self,TESTSET):
CONF=[[0,0,0],[0,0,0],[0,0,0]]
for i in range(len(TESTSET)):
for j in range(len(TESTSET[i])):
Max=-100000000000.0
index=-1
for k in range(3):
if(Max<((self.g_x[k][0]*TESTSET[i][j][0])+(self.g_x[k][1]*TESTSET[i][j][1])+self.g_x[k][2])):
Max=(self.g_x[k][0]*TESTSET[i][j][0])+(self.g_x[k][1]*TESTSET[i][j][1])+self.g_x[k][2]
index=k
CONF[i][index]=CONF[i][index]+1
for i in range(3):
for j in range(3):
print(CONF[i][j], end=" ")
print("")
sf.get_Score(CONF)
def get_ConfMatrix(self, TESTSET):
CONF = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
self.Class1_test_Matrix = sf.get_Matrix(TESTSET[0])
self.Class2_test_Matrix = sf.get_Matrix(TESTSET[1])
self.Class3_test_Matrix = sf.get_Matrix(TESTSET[2])
self.mew = []
for i in range(len(TESTSET)):
self.mew.append(sf.Mean(TESTSET[i]))
# print (self.Class1_test_Matrix,self.Class2_test_Matrix)
inv_class1 = sf.get_Inverse(self.Class1_test_Matrix)
inv_class2 = sf.get_Inverse(self.Class2_test_Matrix)
inv_class3 = sf.get_Inverse(self.Class3_test_Matrix)
temp1 = sf.get_Matrix(TESTSET[0])
temp2 = sf.get_Matrix(TESTSET[1])
temp3 = sf.get_Matrix(TESTSET[2])
# print (temp1,temp2)
for i in range(len(TESTSET)):
for j in range(len(TESTSET[i])):
temp = [0, 0, 0]
val1 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class1, self.mew[0], temp1,
len(TESTSET[0]))
val2 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class2, self.mew[1], temp2,
len(TESTSET[1]))
val3 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class3, self.mew[2], temp3,
len(TESTSET[2]))
if (max(val1, val2, val3) == val1): CONF[i][0] = CONF[i][0] + 1
elif (max(val1, val2, val3) == val2):
CONF[i][1] = CONF[i][1] + 1
else:
CONF[i][2] = CONF[i][2] + 1
for i in range(3):
for j in range(3):
print(CONF[i][j], end=" ")
print("")
sf.get_Score(CONF)
def get_ConfMatrix_pair(self, TESTSET):
CONF=[[0,0],[0,0]]
arr=[0,1]
for i in arr:
for j in range(len(TESTSET[i])):
Max=-100000000000.0
index=-1
for k in arr:
if(Max<((self.g_x[k][0]*TESTSET[i][j][0])+(self.g_x[k][1]*TESTSET[i][j][1])+self.g_x[k][2])):
Max=(self.g_x[k][0]*TESTSET[i][j][0])+(self.g_x[k][1]*TESTSET[i][j][1])+self.g_x[k][2]
index=k
CONF[i][index]=CONF[i][index]+1
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
print("For class1 and 2")
sf.get_Score(CONF)
CONF=[[0,0],[0,0]]
arr=[1,2]
for i in range(2):
for j in range(len(TESTSET[arr[i]])):
Max=-100000000000.0
index=-1
for k in range(2):
if(Max<((self.g_x[arr[k]][0]*TESTSET[arr[i]][j][0])+(self.g_x[arr[k]][1]*TESTSET[arr[i]][j][1])+self.g_x[arr[k]][2])):
Max=((self.g_x[arr[k]][0]*TESTSET[arr[i]][j][0])+(self.g_x[arr[k]][1]*TESTSET[arr[i]][j][1])+self.g_x[arr[k]][2])
index=k
CONF[i][index]=CONF[i][index]+1
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
print("For class2 and 3")
sf.get_Score(CONF)
CONF=[[0,0],[0,0]]
arr=[0,2]
for i in range(2):
for j in range(len(TESTSET[arr[i]])):
Max=-100000000000.0
index=-1
for k in range(2):
if(Max<((self.g_x[arr[k]][0]*TESTSET[arr[i]][j][0])+(self.g_x[arr[k]][1]*TESTSET[arr[i]][j][1])+self.g_x[arr[k]][2])):
Max=((self.g_x[arr[k]][0]*TESTSET[arr[i]][j][0])+(self.g_x[arr[k]][1]*TESTSET[arr[i]][j][1])+self.g_x[arr[k]][2])
index=k
CONF[i][index]=CONF[i][index]+1
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
print("For class1 and 3")
sf.get_Score(CONF)
def get_ConfMatrix_pair(self, TESTSET):
CONF = [[0, 0], [0, 0]]
temp1 = sf.get_Matrix(TESTSET[0])
temp2 = sf.get_Matrix(TESTSET[1])
temp3 = sf.get_Matrix(TESTSET[2])
self.mew = []
for i in range(len(TESTSET)):
self.mew.append(sf.Mean(TESTSET[i]))
inv_class1 = sf.get_Inverse(temp1)
inv_class2 = sf.get_Inverse(temp2)
inv_class3 = sf.get_Inverse(temp3)
self.Class1_test_Matrix = sf.get_Matrix(TESTSET[0])
self.Class2_test_Matrix = sf.get_Matrix(TESTSET[1])
self.Class3_test_Matrix = sf.get_Matrix(TESTSET[2])
# for i in range(len(TESTSET)):
case = [0, 1]
for i in case:
for j in range(len(TESTSET[i])):
temp = [0, 0, 0]
val1 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class1, self.mew[0],
self.Class1_test_Matrix, len(TESTSET[0]))
val2 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class2, self.mew[1],
self.Class2_test_Matrix, len(TESTSET[1]))
if (val1 > val2): CONF[i][0] = CONF[i][0] + 1
else: CONF[i][1] = CONF[i][1] + 1
print("Confusion Matrix for class 1 & 2")
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
sf.get_Score(CONF)
CONF = [[0, 0], [0, 0]]
case = [1, 2]
for i in case:
for j in range(len(TESTSET[i])):
temp = [0, 0, 0]
val2 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class2, self.mew[1],
self.Class2_test_Matrix, len(TESTSET[1]))
val3 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class3, self.mew[2],
self.Class3_test_Matrix, len(TESTSET[2]))
if (val2 > val3): CONF[i - 1][0] = CONF[i - 1][0] + 1
else: CONF[i - 1][1] = CONF[i - 1][1] + 1
print("Confusion Matrix for class 2 & 3")
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
sf.get_Score(CONF)
CONF = [[0, 0], [0, 0]]
case = [0, 2]
for i in case:
for j in range(len(TESTSET[i])):
temp = [0, 0, 0]
val1 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class1, self.mew[0],
self.Class1_test_Matrix, len(TESTSET[0]))
val3 = self.getGx(TESTSET[i][j][0], TESTSET[i][j][1],
inv_class3, self.mew[2],
self.Class3_test_Matrix, len(TESTSET[2]))
k = 0
if (i == 2): k = 1
if (val1 > val3): CONF[k][0] = CONF[k][0] + 1
else: CONF[k][1] = CONF[k][1] + 1
print("Confusion Matrix for class 2 & 3")
for i in range(2):
for j in range(2):
print(CONF[i][j], end=" ")
print("")
sf.get_Score(CONF)