Linearly separable data is data that if graphed in two dimensions, can be separated by a straight line. ... This data is linearly separable because there is a straight line from lower left to upper right that separates the red and blue data. Neither of these two datasets is linearly separable.
How do you know if data is linearly separable?
The recipe to check for linear separability is:
- Instantiate a SVM with a big C hyperparameter (use sklearn for ease).
- Train the model with your data.
- Classify the train set with your newly trained SVM.
- If you get 100% accuracy on classification, congratulations! Your data is linearly separable.
What is not linearly separable?
The right one is separable into two parts for A' and B` by the indicated line. I.e. You cannot draw a straight line into the left image, so that all the X are on one side, and all the O are on the other. That is why it is called "not linearly separable" == there exist no linear manifold separating the two classes.
