Difference between classification and regression score in Python scikit learn

Question

I a, new for python scikit learning I develop a data mining algorithm using scikit learn classification methods and now i need to find its accuracy. first just need to know,

What is difference between classification and regression score in Python scikit learn?

Is there any other way that i can calculate accuracy of my prediction algorithm?

r2_score(y_test,predictions)
f1_score(y_test,predictions)

Regression score (%)== 66%
Classification score (%) == 75%

Answer 1

Classification Score is used for discrete values , having distinct class labels,like yes or no, survived, not survived
whereas Regression score is used for continuous values, like prediction house prices, weather conditions.