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What Goes before the CART? Introducing Classification Trees with Arbor and CODAP
- Source :
-
Teaching Statistics: An International Journal for Teachers . Sum 2023 45(1):S104-S113. - Publication Year :
- 2023
-
Abstract
- This volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how they work, and how well. This build-it-yourself process is more transparent than using algorithms such as CART; we believe it will help students not only understand the fundamentals of trees, but also better understand tree-building algorithms when they do encounter them. And because classification is an important task in machine learning, a good foundation in trees can prepare students to better understand that emerging and important field. We also describe a free online tool--Arbor--that students can use to do this, and note some implications for instruction.
Details
- Language :
- English
- ISSN :
- 0141-982X and 1467-9639
- Volume :
- 45
- Issue :
- 1
- Database :
- ERIC
- Journal :
- Teaching Statistics: An International Journal for Teachers
- Publication Type :
- Academic Journal
- Accession number :
- EJ1384198
- Document Type :
- Journal Articles<br />Reports - Descriptive
- Full Text :
- https://doi.org/10.1111/test.12347