Difference between classification and regression score in Python scikit learn

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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%
Feb 24 in Machine Learning by Dev
• 6,000 points
45 views

1 answer to this question.

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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.
answered Feb 24 by Nandini
• 5,480 points

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