Query Regarding Logistic Regression Visualization

Course Q&A Natural Language Processing NLP with Classification and Vector Spaces
1

In the Visualizing Tweets and Logistic Regression models lab, one of the cells reads:

The vector theta represents a plane that split our feature space into two parts. Samples located over that plane are considered positive, and samples located under that plane are considered negative.

Can someone please explain this statement? I am not really well-versed in calculus. If you can hook me up to relevant resources, that would help too.

Thank you

2

Hello @Muhammad_Sajawal_Sia,

This question seems to be for NLP Course 1 Week 1, so I have moved it for you to that category.

Raymond

3

Hi @Muhammad_Sajawal_Sia

The basic idea is that this vector theta is enough to describe some plane, that splits the space into two parts (positive and negative).

Later in the course it is somewhat explained in this lecture.

But if you want a simple concise explanation I would suggest this video.

Cheers

4

Thank you for your help.