# sortmat: Sort matrix or data frame In penalizedSVM: Feature Selection SVM using penalty functions

## Description

A useful function for ranking. Sort matrix or dataframe 'Mat', by column(s) 'Sort' in decrising or increasing order.

## Usage

 `1` ```sortmat (Mat, Sort, decreasing=FALSE) ```

## Arguments

 `Mat` a matrix or a data frame `Sort` Sort is a number ! `decreasing` in decreasing order? default: FALSE

## Value

sorted matrix or data frame

## Author(s)

found in world wide web: http://tolstoy.newcastle.edu.au/R/help/99b/0668.html

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42``` ```m <- matrix(c(9:5, c(1, 4, 3, 3, 5), c(1, 2, 4, 3, 5)), ncol = 3, byrow = FALSE) print( m) # [,1] [,2] [,3] #[1,] 9 1 1 #[2,] 8 4 2 #[3,] 7 3 4 #[4,] 6 3 3 #[5,] 5 5 5 # sort first according to the second column then if equal according to the third column print(m1 <- sortmat(Mat = m, Sort = c(2, 3))) # [,1] [,2] [,3] #[1,] 9 1 1 #[2,] 6 3 3 #[3,] 7 3 4 #[4,] 8 4 2 #[5,] 5 5 5 # sort first according to the third (!) column then if equal according # to the second column print(m2 <- sortmat(Mat = m, Sort = c(3, 2))) # [,1] [,2] [,3] #[1,] 9 1 1 #[2,] 8 4 2 #[3,] 6 3 3 #[4,] 7 3 4 #[5,] 5 5 5 # Note m1 and m2 are not equal!!!! all(m1==m2) #FALSE # in decreasing order print(m3 <- sortmat(Mat = m, Sort = c(2, 3), decreasing=TRUE)) # [,1] [,2] [,3] #[1,] 5 5 5 #[2,] 8 4 2 #[3,] 7 3 4 #[4,] 6 3 3 #[5,] 9 1 1 ```

penalizedSVM documentation built on May 30, 2017, 4:11 a.m.