# Sampling_via_cluster: Stratified sampling by clusters or types In bishun945/FCMm: Fuzzy Cluster Method Based on the Optimized m Value (Fuzzifier)

## Description

Stratified sampling by clusters or types

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```Sampling_via_cluster( x, num = length(x), replace = FALSE, order.value = NULL, ... ) Sampling_by_sort( x, num = length(x), log10 = FALSE, n_group = 3, replace = TRUE ) ```

## Arguments

 `x` A vector represents the cluster or type, only support numeric value now. `num` The number of sampling. Default as `length(x)` `replace` The way of sampling. See `help(sample)` for more details. `order.value` The vector used for ordering. Default is `NULL`. `...` Parameters of function `Sampling_by_sort`. `log10` Whether to log10-trans the `order.value`. Default is `FALSE`. `n_group` Number of group to be devided. Default is 3.

## Value

Result of `Sampling_via_cluster` is the index of sampled items from the input `x`.

Other Algorithm assessment: `Assessment_via_cluster()`, `Getting_Asses_results()`, `Score_algorithms_interval()`, `Score_algorithms_sort()`, `Scoring_system()`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```library(FCMm) x = round(runif(100, 1, 10)) table(x) w_sampled = Sampling_via_cluster(x, 20) table(x[w_sampled]) set.seed(1) N <- 100 x <- stats::rlnorm(N) ind1 <- Sampling_by_sort(x, N/2) ind2 <- sample.int(length(x), N/2) library(ggplot2) ggplot() + geom_density(aes(x = x, color = "Total")) + geom_density(aes(x = x[ind1], color = "ind1"), alpha = 0.8) + geom_density(aes(x = x[ind2], color = "ind2"), alpha = 0.6) + scale_x_log10() ```