---
title: "Sparsifying Knowledge-Graph Using Target Information"
url: https://daily.dev/posts/sparsifying-knowledge-graph-using-target-information-1hb7hakoi
source_url: https://towardsdatascience.com/sparsifying-knowledge-graph-using-target-information-8fb1014cbb0f
type: article
source: "Towards Data Science"
published: 2024-05-08T17:48:25.368Z
updated: 2024-05-09T08:03:37.463Z
tags: ["machine-learning", "feature-engineering"]
reading_time: 4
upvotes: 0
comments: 0
language: en
---

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# Sparsifying Knowledge-Graph Using Target Information

**[Towards Data Science](https://daily.dev/sources/tds)** · 4 min read · 0 upvotes · 0 comments

## Summary

This post discusses the use of Pointwise Mutual Information (PMI) to sparsify knowledge graphs in supervised machine learning tasks. It explains the need for graph sparsification and provides a concrete example using medical data. The post also delves into the details of using PMI to assess the relevance of edges in the graph and remove irrelevant edges. It concludes with caveats and potential improvements when using PMI for graph sparsification.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/sparsifying-knowledge-graph-using-target-information-8fb1014cbb0f>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#feature-engineering](https://daily.dev/tags/feature-engineering)

[View this post on daily.dev](https://daily.dev/posts/sparsifying-knowledge-graph-using-target-information-1hb7hakoi)
