[MINI] Conditional Independence
Data Skeptic21 Jul 2017

[MINI] Conditional Independence

In statistics, two random variables might depend on one another (for example, interest rates and new home purchases). We call this conditional dependence. An important related concept exists called conditional independence. This phrase describes situations in which two variables are independent of one another given some other variable.

For example, the probability that a vendor will pay their bill on time could depend on many factors such as the company's market cap. Thus, a statistical analysis would reveal many relationships between observable details about the company and their propensity for paying on time. However, if you know that the company has filed for bankruptcy, then we might assume their chances of paying on time have dropped to near 0, and the result is now independent of all other factors in light of this new information.

We discuss a few real world analogies to this idea in the context of some chance meetings on our recent trip to New York City.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(601)

Sustainable Recommender Systems for Tourism

Sustainable Recommender Systems for Tourism

In this episode, we speak with Ashmi Banerjee, a doctoral candidate at the Technical University of Munich, about her pioneering research on AI-powered recommender systems in tourism. Ashmi illuminates...

9 Okt 202538min

Interpretable Real Estate Recommendations

Interpretable Real Estate Recommendations

In this episode of Data Skeptic's Recommender Systems series, host Kyle Polich interviews Dr. Kunal Mukherjee, a postdoctoral research associate at Virginia Tech, about the paper "Z-REx: Human-Interpr...

22 Sep 202532min

Why Am I Seeing This?

Why Am I Seeing This?

In this episode of Data Skeptic, we explore the challenges of studying social media recommender systems when exposure data isn't accessible. Our guests Sabrina Guidotti, Gregor Donabauer, and Dimitri ...

8 Sep 202549min

Eco-aware GNN Recommenders

Eco-aware GNN Recommenders

In this episode of Data Skeptic, we dive into eco-friendly AI with Antonio Purificato, a PhD student from Sapienza University of Rome. Antonio discusses his research on "EcoAware Graph Neural Networks...

30 Aug 202544min

Networks and Recommender Systems

Networks and Recommender Systems

Kyle reveals the next season's topic will be "Recommender Systems".  Asaf shares insights on how network science contributes to the recommender system field.

17 Aug 202517min

Network of Past Guests Collaborations

Network of Past Guests Collaborations

Kyle and Asaf discuss a project in which we link former guests of the podcast based on their co-authorship of academic papers.

21 Jul 202534min

The Network Diversion Problem

The Network Diversion Problem

In this episode, Professor Pål Grønås Drange from the University of Bergen, introduces the field of Parameterized Complexity - a powerful framework for tackling hard computational problems by focusing...

6 Jul 202546min

Complex Dynamic in Networks

Complex Dynamic in Networks

In this episode, we learn why simply analyzing the structure of a network is not enough, and how the dynamics - the actual mechanisms of interaction between components - can drastically change how inf...

28 Jun 202556min

Populært innen Vitenskap

fastlegen
tingenes-tilstand
jss
forskningno
rekommandert
rss-zahid-ali-hjelper-deg
rss-paradigmepodden
sinnsyn
vett-og-vitenskap-med-gaute-einevoll
rss-overskuddsliv
nordnorsk-historie
kvinnehelsepodden
tidlose-historier
villmarksliv
liberal-halvtime
rss-inn-til-kjernen-med-sunniva-rose
fjellsportpodden
grunnstoffene
nevropodden
rss-rekommandert