Question

Given a binary classification dataset, say having Y = 1 or 0 as the target variable and X 1 and X 2 as two numeric attributes, what does it mean to say that the dataset is linearly separable?

Answer 1

Answer:

A straight line aX1+bX2+c=0 can separate the points Y=0 from Y=1

Explanation:

A dataset is linearly separable when the different classes can be separated using a line. Here, classes 0 and 1 are being separated by the given equation of line.

Answer 2

Depends on the data set

Explanation:

• Depending on the data set, if the data can be separated by a straight line (f(x)=w1x1+w2x2+w0) then we can say that the dataset is linearly separable.
• In this case all the points which belongs to y=0, f(x)>0 and in y=1, f(x)<0.  And if the datasets can't be separated by a line, then we will say that the datasets are non-linearly separable.

hence, Depends on the data set