View source: R/visualization_fuzzycluster.R
visualization_fuzzycluster | R Documentation |
Visualize results from fuzzy clusters with line chart
visualization_fuzzycluster( input_data, group, group_levels, k_cluster, iteration = 100, mfrow = c(3, 3), min_mem = 0.1, plot = TRUE )
input_data |
a data frame containing ID and expression profile. |
group |
a factor for representing groups. |
group_levels |
a factor levels for group. |
k_cluster |
number of clusters fuzzy cluster. |
iteration |
a numeric value for interation, the defualt is 100. |
mfrow |
a vector containing 2 elements for controling the subplots in graphic window, the default is mfrow = c(3,3) |
min_mem |
cutoff value for membership. Only results with greater than min_mem are showed. |
plot |
a boolean value for deciding whether ploting, the default is TRUE. |
A lines chart with fuzzy degree.
Dongdong Zhan and Mengsha Tong
(1) David Meyer, Evgenia Dimitriadou, Kurt Hornik, Andreas Weingessel and Friedrich Leisch (2017). e1071: Misc Functions of the \ Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien. R package version 1.6-8.https://CRAN.R-project.org/package=e1071 \ (2) Pengyi Yang (2018). ClueR: Cluster Evaluation. R package version 1.4. https://CRAN.R-project.org/package=ClueR
## The process needs to load data from PhosMap datasets stored into FTP server and perform large computation. ## It may take a few minutes. if(FALSE){ ftp_url <- "ftp://111.198.139.72:4000/pub/PhosMap_datasets/function_demo_data/visualization_fuzzycluster.RData" load_data <- load_data_with_ftp(ftp_url, 'RData') writeBin(load_data, "visualization_fuzzycluster.RData") load("visualization_fuzzycluster.RData") fuzzy_clustObj <- visualization_fuzzycluster( fuzzy_input_df, group, group_levels, k_cluster=9, iteration = 100, mfrow = c(3,3), min_mem = 0.1 ) }
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