def combtn_fun(self):
dataset = ["50-50", "70-30", "80-20"]
svm = []
bp = []
gsa = []
plot = []
x = [50, 70, 80]
for i in dataset:
acc1, sens1, cm1 = svm_breastdev.predict(dataset=i)
acc2, sens2, cm2 = bp_breastdev.predict(dataset=i)
acc, fet_sub = gsadev.predict(dataset=i)
svm.append(acc1)
bp.append(acc2)
gsa.append(acc)
plt.plot(x, svm, label="SVM")
plt.plot(x, bp, label="BP")
plt.plot(x, gsa, label="GSA")
plt.xlabel("Training Set (%)")
plt.ylabel("Accuracy")
plt.title("Algorithm Comparision")
plt.legend()
plt.legend(bbox_to_anchor=(1.05, 1), loc=1, borderaxespad=0.)
plt.show()
def combtn1_fun(self):
ker = ["rbf", "poly", "sigmoid"]
dataset = ["50-50", "70-30", "80-20"]
C = str(self.le_c.text())
gamma = str(self.le_gamma.text())
c_float = eval(C)
gamma_float = eval(gamma)
plot = []
x = [50, 70, 80]
for i in ker:
v = []
for j in dataset:
acc, sens, cm = svm_breastdev.predict(i, j, c_float,
gamma_float)
v.append(acc)
plot.append(v)
a = 0
#print plot
for i in plot:
plt.plot(x, i, label=ker[a])
a += 1
plt.xlabel("Training Set (%)")
plt.ylabel("Accuracy")
plt.title("Kernel Comparision")
plt.legend()
plt.legend(bbox_to_anchor=(1.05, 1), loc=1, borderaxespad=0.)
plt.show()
def crbtn1_fun(self):
kernel = str(self.cb1.currentText())
print "kernel ", kernel
dataset = str(self.cb2.currentText())
print "dataset ", dataset
C = str(self.le_c.text())
print "C ", C
gamma = str(self.le_gamma.text())
print "gamma ", gamma
c_float = eval(C)
gamma_float = eval(gamma)
print c_float, gamma_float
acc, sens, cm = svm_breastdev.predict(kernel, dataset, c_float,
gamma_float)
self.res1.append("Confusion Matrix:")
self.res1.append("\t\tBenign\tMalignant")
self.res1.append("Benign\t\t" + str(cm[0][0]) + "\t" + str(cm[0][1]))
self.res1.append("Malignant\t\t" + str(cm[1][0]) + "\t" +
str(cm[1][1]))
self.res1.append("\nAccuracy : " + str(round(acc * 100, 2)) + "%")
self.res1.append("\nSenstivity :\n" + "Benign: " +
str(round(sens[0] * 100, 2)) + "%")
self.res1.append("Malignant: " + str(round(sens[1] * 100, 2)) + "%\n")
plot.predict(kernel, dataset, c_float, gamma_float)