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In this post, we will understand the difference between classification and regression.

It gives out discrete values.

Given a group of data, this method helps group the data into different groups.

This grouping is done based on different criterion.

It is unordered.

The mapping function is used to map values to pre-defined classes.

Example are: Decision tree, logistic regression.

It gives continuous values.

It uses the mapping function to map values to continuous output.

It is ordered.

It has dependent and independent variables.

It tries to find a best fit line.

It tries to extrapolate the graph to find/predict the values.

It is done using the root mean square error method.

Examples are: Regression tree (Random forest), Linear regression

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