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# Dmitry Grapovdgrapov

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Last active Nov 29, 2019
Self-organizing map (SOM) example in R
View SOM example.R
 #SOM example using wines data set library(kohonen) data(wines) set.seed(7) #create SOM grid sommap <- som(scale(wines), grid = somgrid(2, 2, "hexagonal")) ## use hierarchical clustering to cluster the codebook vectors groups<-3
Created Feb 2, 2018
Example of a shiny app with data upload and different plot options
View example.R
 #initialize library(shiny) library(ggplot2) library(purrr) library(dplyr) #example data data(iris)
Last active Jun 19, 2019
ggplot2 to plotly to shiny to box/lasso select to DT
View plotly_select_DT.R
 #plotly box or lasso select linked to # DT data table # using Wage data # the out group: is sex:Male, region:Middle Atlantic + library(ggplot2) library(plotly) library(dplyr) library(ISLR)
Created May 22, 2019
Data Science Exercise
View gist:d15aedea295f32fa43d76b0a864c577b
 DATA SCIENCE EXERCISE The following challenge requires the beer reviews data set called beer_reviews.csv. This data set can be downloaded from the following site: https://data.world/socialmediadata/beeradvocate . Note you can create a free temporary account to download this .csv. Questions to answer using this data: Which brewery produces the strongest beers by ABV%? If you had to pick 3 beers to recommend using only this data, which would you pick? Which of the factors (aroma, taste, appearance, palette) are most important in determining the overall quality of a beer? Additional math/coding question unrelated to the data:
Last active Mar 22, 2019
Orthogonal Signal Correction for PLS models (OPLS)
View Orthogonal Signal Correction (OSC) for PLS models OSC-PLS (OPLS)
 #see updated code base and some examples in the function "test" # https://github.com/dgrapov/devium/blob/master/R/Devium%20PLS%20%20and%20OPLS.r #Orthogonal Signal Correction for PLS models (OPLS) #adapted from an example in the book "Chemometrics with R by Ron Wehrens" #this code requires the following packages: need.packages<-c("pls", # to generate PLS models "ggplot2" ) # to plot results
Last active Oct 31, 2018
PCA using Shiny. http://spark.rstudio.com/dgrapov/PCA/
View global.R
 #check for and/or install dependencies need<-c("RCurl","ggplot2","gridExtra","reshape2") for(i in 1:length(need)){ if(require(need[i], character.only = TRUE)==FALSE){ install.packages(need[i]);library(need[i], character.only = TRUE)} else { library(need[i],character.only = TRUE)} } if(require(pcaMethods)==FALSE){ need<-c('Rcpp', 'rJava', 'Matrix', 'cluster', 'foreign', 'lattice', 'mgcv', 'survival') for(i in 1:length(need)){
Created Apr 6, 2018
Deep error
View replace_in.R
 > in Error: unexpected 'in' in "in"
Created Mar 24, 2018
basic principal components analysis and visualization in R
View pca.R
 # Basic PCA example # use www.createdatasol.com for # an advanced user interface #required packages for plotting library(ggplot2) library(ggrepel) #load data data<-read.csv('~/Sampledata.csv',
Last active Mar 2, 2018
View Andrews plots and encoding.r
 #needed packages library(andrews) library(ggplot2) #get some data here I use "mtcars" data<-mtcars fct<-as.factor(mtcars\$cyl) # factor for intial grouping #get andrews encoding (x and y coords)
Created Jan 10, 2018
fast (?) implementations of tanimoto distance calculations
View tanimoto.R
 #' @title fast_tanimoto #' @param mat matrix or data frame of numeric values #' @param output 'matrix' (default) or 'edge list' (non-redundant and undirected) #' @param progress TRUE, show progress #' @imports reshape2 fast_tanimoto<-function(mat,output='matrix',progress=TRUE){ mat[is.na(mat)]<-0 #scoring function score<-function(x){sum(x==2)/sum(x>0)}
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