TY  - RPRT
U1  - Arbeitspapier
A1  - Engel, Joachim
A1  - Erickson, Tim
T1  - What goes before the CART? Introducing classification trees with Arbor and CODAP
N2  - 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.
KW  - Statistik
KW  - Unterricht
KW  - classification trees, Arbor
Y1  - 2023
U6  - https://doi.org/10.1111/test.12347
DO  - https://doi.org/10.1111/test.12347
N1  - Volltext ist unter angegebenem DOI abrufbar.
IS  - TEACHING STATISTICS 45, S1
PB  - Wiley Online Library
ER  -