# Formulating the Support Vector Machine Optimization Problem

DevFeed: [Formulating the Support Vector Machine Optimization Problem](<https://devfeed.tech/articles/formulating-the-support-vector-machine-optimization-problem-40411.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2017/06/05/formulating-the-support-vector-machine-optimization-problem/>)

Published: 2017-06-05T08:00:46Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Optimization](<https://devfeed.tech/topics/optimization.md>), [math](<https://devfeed.tech/topics/math.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [data](<https://devfeed.tech/topics/data.md>)

Tags: [blog-post](<https://devfeed.tech/tags/blog-post.md>), [data-visualization](<https://devfeed.tech/tags/data-visualization.md>), [inner-product](<https://devfeed.tech/tags/inner-product.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [math](<https://devfeed.tech/tags/math.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [programming](<https://devfeed.tech/tags/programming.md>), [support-vector-machines](<https://devfeed.tech/tags/support-vector-machines.md>)

## AI overview

A tutorial formulates the support vector machine optimization problem using separating hyperplanes, labeled training data, vector-and-scalar bias terms, and the goal of choosing a separator that generalizes well.

## Source excerpt

The hypothesis and the setup This blog post has an interactive demo (mostly used toward the end of the post). The source for this demo is available in a Github repository. Last time we saw how the inner product of two vectors gives rise to a decision rule: if $ w$ is the normal to a line (or hyperplane) $ L$, the sign of the inner product $ \langle x, w \rangle$ tells you whether $ x$ is on the same side of $ L$ as $ w$.