Need help to create Confusion Matrix and Prediction Code

Question

model_SVC = SVC(C=1000,gamma=0.1, kernel='rbf')
model_SVC.fit(X_train,Y_train) #CASIA2

predictions=model_SVC.predict(X_test)

print(accuracy_score(Y_test,predictions))
print(confusion_matrix(Y_test,predictions))
print(classification_report(Y_test,predictions))

I need help in creating a confusion matrix using seaborn and a code to predict the image. Can someone help me with this?

Answer 1

I have used your code along with some random code to generate data and ConfusionMatrixDisplay to generate the confusion matrix. You can change the parameters as required to suit your needs.

import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report
from sklearn.datasets import make_classification
from sklearn.metrics import ConfusionMatrixDisplay, confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC

X, y = make_classification(random_state=0)
X_train, X_test, Y_train, Y_test = train_test_split(X, y, random_state=0)

model_SVC = SVC(C=1000,gamma=0.1, kernel='rbf')
model_SVC.fit(X_train,Y_train) #CASIA2

predictions=model_SVC.predict(X_test)

#print(accuracy_score(Y_test,predictions))
cm = confusion_matrix(Y_test,predictions)
#print(classification_report(Y_test,predictions))

disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=model_SVC.classes_)
font={'size':'14'}
plt.rc('font',**font)
plt.rcParams['figure.figsize']=[6,6]
disp.plot(cmap='Blues',values_format='0.2f')
#plt.colorbar(im,fraction=0.046, pad=0.04)
plt.show()

Plot