Python SCV

[ranjjeetk]

I have below task to be completed.

1. Import two modules sklearn.datasets, and sklearn.model_selection.
   
   Load popular digits dataset from sklearn.datasets module and assign it to variable digits.
   
   Split digits.data into two sets names X_train and X_test. Also, split digits.target into two sets Y_train and Y_test.
   
   Hint: Use train_test_split method from sklearn.model_selection; set random_state to 30; and perform stratified sampling.
   Print the shape of X_train dataset.
   
   Print the shape of X_test dataset.
   
   Import required module from sklearn.svm.
   
   Build an SVM classifier from X_train set and Y_train labels, with default parameters. Name the model as svm_clf.
   
   Evaluate the model accuracy on testing data set and print it's score.
   
   Import required module from sklearn.svm.
   
   Build an SVM classifier from X_train set and Y_train labels, with default parameters. Name the model as svm_clf.
   
   Evaluate the model accuracy on testing data set and print it's score.
   

I wrote below code but something in last three points is still missing. Can you help.

import sklearn.datasets as datasets

from sklearn.model_selection import train_test_split

digits = datasets.load_digits()

X_train, X_test, Y_train, Y_test = train_test_split(digits.data, digits.target, random_state =30)

print(X_train.shape)

print(X_test.shape)

from sklearn.svm import SVC
svm_clf = SVC()
svm_clf = svm_clf.fit(X_train, Y_train)
print(svm_clf.score(X_train,Y_train))
svm_clf = svm_clf.fit(X_test, Y_test)
print(svm_clf.score(X_test,Y_test))

from sklearn.metrics import accuracy_score
Y_pred_test = svm_clf.predict(X_test)
print(accuracy_score(Y_test, Y_pred_test))