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Seeing the Random Forest behind the Trees

This article is part of a BAI series exploring 10 basic machine learning algorithms

How can you predict for which machine learning algorithm I’m looking? In the parlor game of twenty questions the goal is to find the answer by asking the minimum number of categorical yes/no questions. Which question should you ask first, and on what criteria? Which question should be asked next? What is the minimum number of questions needed to insure the correct prediction? Keep this game in mind as we explore how the Random Forest algorithm is used in machine learning, its basic assumptions and use scenarios, as well as what precautions we should take when relying on this methodology...

Dr. Lee SCHLENKER
Principal


 In this issue :

Find that Panda

Seeing the Random Forest...

Let's explore how Random Forest is used in machine learning, as well as its basic assumptions and use scenarios

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The BAI Spring Session

BAI Community News

In brief, the recent projects, conferences, bootcamps and publicatons of the BAI Data Science Community

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The Business Analytics Institute

The  Practice of Data Science

In challenging the participants to think out of the box, the pedagogical program of tthe BAI Summer School will focus on workshops and case studies drawn from Health Analytics, Smart Cities, and Logistics.

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 The Ambassador Program

Analytics in Action

BAI faculty facilitated a key module again this year in SDMIMD’s Analytics Track, Analytics in Action, in Mysore, India. 

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The Paradox of Trust

Partner Interview - Sergi Sergiev

Sergi Sergiev is the Head of the Data Science Society and  founder of ShopUp, an IT Services company that specializes in IoT customer analytics in the retail sector.

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 Airport Excellence

Trust by Design

The motor of the next industrial revolution won't be data, but trust...

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This Newsletter has been created specifically for the BAI community to foster conversation around the use of analytics in improving business decision-making. 

Interested in our February Newsletter? It can be found here