19.1 Clustering Setup
THIS SECTION IS UNDER DEVELOPMENT. PLEASE CHECK BACK LATER
The rattle::weatherAUS dataset is loaded into the template
variable ds and further template variables are setup as
introduced by Graham J. Williams (2017). See
Chapter 8 for details.
dsname <- "weatherAUS"
ds <- get(dsname)
nobs <- nrow(ds)
vnames <- names(ds)
ds %<>% clean_names(numerals="right")
names(vnames) <- names(ds)
vars <- names(ds)
target <- "rain_tomorrow"
vars <- c(target, vars) %>% unique() %>% rev()It is always useful to remind ourselves of the dataset with a random sample:
## # A tibble: 275,410 × 7
## date location risk_mm rain_tomorrow max_temp pressure_3pm sunshine
## <date> <chr> <dbl> <fct> <dbl> <dbl> <dbl>
## 1 2021-11-04 Townsville 0 No 30.7 1013. NA
## 2 2015-05-19 WaggaWagga 9.6 Yes 19 1013. 1.6
## 3 2017-11-30 Richmond 0.2 No 31.7 1014. NA
## 4 2010-02-15 Hobart 0 No 25.5 1018. 12.4
## 5 2026-01-01 Sydney 3 Yes 21.5 1016. 0
## 6 2025-07-07 Woomera 0 No 19.4 1016. NA
....References
Williams, Graham J. 2017. The Essentials of Data Science: Knowledge Discovery Using r. The r Series. CRC Press.
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