NaiveBayes: Find first non-missing element

In sidiwang/classifier: Naive Bayes Classifier (Multinomial, Gaussian)

Description

Given a set of vectors, 'coalesce()' finds the first non-missing value at each position. This is inspired by the SQL 'COALESCE' function which does the same thing for 'NULL's.

Usage

NaiveBayes(x, ...)

Arguments

...	Vectors. All inputs should either be length 1, or the same length as the first argument. These dots support [tidy dots][rlang::tidy-dots] features.

Value

A vector the same length as the first '...' argument with missing values replaced by the first non-missing value.

See Also

[na_if()] to replace specified values with a 'NA'. [tidyr::replace_na()] to replace 'NA' with a value

Examples

# Use a single value to replace all missing values
x <- sample(c(1:5, NA, NA, NA))
coalesce(x, 0L)

# Or match together a complete vector from missing pieces
y <- c(1, 2, NA, NA, 5)
z <- c(NA, NA, 3, 4, 5)
coalesce(y, z)

# Supply lists by splicing them into dots:
vecs <- list(
  c(1, 2, NA, NA, 5),
  c(NA, NA, 3, 4, 5)
)
coalesce(!!!vecs)

sidiwang/classifier documentation built on Nov. 23, 2019, 12:06 a.m.