# Search Results

VC dimension

In Vapnik–Chervonenkis theory, the Vapnik–Chervonenkis (VC) dimension is a measure of the capacity of a set of ...

Choose what you’re giving feedback on

Or give general feedback

Vapnik–Chervonenkis dimension

### Images

## Description

In Vapnik–Chervonenkis theory, the Vapnik–Chervonenkis dimension is a measure of the capacity of a set of functions that can be learned by a statistical binary classification algorithm. It is defined as the cardinality of the largest set of points that the algorithm can shatter. Wikipedia

Jun 2, 2018

3 answersI'm studying machine learning from Andrew Ng Stanford lectures and just came across the theory of VC dimensions. According to the lectures and ...

How to calculate VC-dimension? - Data Science Stack Exchange

Jan 6, 2017

With regards to VC-dimension, why can you shatter 3 points with ...

Jul 25, 2017

Why the VC dimension to this linear hypothesis equal to 3? - Data ...

Oct 2, 2018

VC dimension of half spaces over the real line - Data Science Stack ...

Jun 30, 2019

More results from datascience.stackexchange.com

Apr 23, 2018 — The VC dimension of a classifier is defined by Vapnik and Chervonenkis to be the cardinality (size) of ...

VC dimension is a formal measure of bias which has played an important role in mathematical work on learnability.