Published in

Bayesian Networks — Independencies and I-maps

In two former articles, we looked at both how we can represent Bayesian Networks in a compact form by using factorization and different reasoning patterns. In this article, we will take a look at independencies and I-maps in Bayesian Networks.

Independencies in Bayesian Networks

We will once more consider the example from the former article once more, which is given by:




Data Scientists must think like an artist when finding a solution when creating a piece of code. ⚪️ Artists enjoy working on interesting problems, even if there is no obvious answer ⚪️ 🔵 Follow to join our 18K+ Unique DAILY Readers 🟠

Recommended from Medium

PAWN 3.0 — Backtest Results

Make big data and AI easy with Microsoft Azure Databricks

Download In #&PDF Pro Power BI Desktop Read !book %ePub

Predictive Maintenance Services and Solutions

Interactive COVID19 report with RMarkdown, Plotly, Leaflet and Shiny

Geopandas Hands-on: Geospatial Data Visualization and Intro to Geometry

Combining Multiple Indonesia Administrative Levels in Single Tableau Worksheet

Serverless Machine Learning Pipelines with Vertex AI: An Introduction

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Helene Kegel

Helene Kegel

More from Medium

Bayesian Networks — Reasoning Patterns

How L1 regularization brings sparsity

Conditional Independence

Ethical AI III: Explainable AI