Explain the difference between Classification and Regression

Data Science, AI and ML
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#1

Classification and Regression Difference

#2

The target variable in classification is continuous whereas in regression it is categorical.

#3

Differences Between Classification and Regression

  1. The Classification process models a function through which the data is predicted in discrete class labels. On the other hand, regression is the process of creating a model which predict continuous quantity.
  2. The classification algorithms involve decision tree, logistic regression, etc. In contrast, regression tree (e.g. Random forest) and linear regression are the examples of regression algorithms.
  3. Classification predicts unordered data while regression predicts ordered data.
  4. Regression can be evaluated using root mean square error. On the contrary, classification is evaluated by measuring accuracy.