20.69 The Original C5.0 Implementation
The (Kuhn and Quinlan 2023) package interfaces the original C code of the C5.0 implementation by Ross Quinlan, the developer of the decision tree induction algorithm.
##
## Call:
## C5.0.formula(formula=form, data=ds[tr, vars])
##
## Classification Tree
## Number of samples: 158807
## Number of predictors: 20
##
## Tree size: 1007
##
## Non-standard options: attempt to group attributes## Overall
## humidity_3pm 100.00
## wind_gust_speed 94.25
## sunshine 85.91
## rain_today 79.39
## pressure_3pm 50.77
## cloud_3pm 33.35
## rainfall 32.90
## pressure_9am 26.86
## wind_dir_3pm 23.18
## max_temp 22.79
## temp_9am 13.83
## humidity_9am 12.01
## temp_3pm 11.70
## wind_dir_9am 11.39
## min_temp 10.35
## wind_gust_dir 9.78
## wind_speed_3pm 8.23
## wind_speed_9am 6.73
## cloud_9am 6.16
## evaporation 1.76% DONT EVAL YET - SEEMS TO BE TAKING LONG TIME
I am not aware of any converter from a C5.0 tree to an rpart tree and so fancyRpartPlot() will not be useful here.
References
Kuhn, Max, and Ross Quinlan. 2023. C50: C5.0 Decision Trees and Rule-Based Models. https://topepo.github.io/C5.0/.
Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0
