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pluginName = SSJ Functions | |
provider = com.github.cbsti | |
thirdparty.list = ssj | |
thirdparty.ssj.Name = SSJ: Stochastic Simulation in Java 2.6 | |
thirdparty.ssj.Copy = Copyright (C) 2008 Pierre L'Ecuyer and Université de Montréal | |
thirdparty.ssj.License = GPL | |
thirdparty.ssj.URL = http://www.iro.umontreal.ca/~simardr/ssj/indexe.html |
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# Load the raw training data and replace missing values with NA | |
training.data.raw <- read.csv('train.csv',header=T,na.strings=c("")) | |
# Output the number of missing values for each column | |
sapply(training.data.raw,function(x) sum(is.na(x))) | |
# Quick check for how many different values for each feature | |
sapply(training.data.raw, function(x) length(unique(x))) | |
# A visual way to check for missing data |
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// create file: | |
sudo vim /usr/share/applications/intellij.desktop | |
// add the following | |
[Desktop Entry] | |
Version=13.0 | |
Type=Application | |
Terminal=false | |
Icon[en_US]=/home/rob/.intellij-13/bin/idea.png | |
Name[en_US]=IntelliJ |
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# Example: Easily source a Gist from R using devtools | |
# 1) install devtools | |
if (!("devtools" %in% installed.packages()[, 1])) { | |
install.packages("devtools") | |
} | |
# 2) source | |
# library(devtools) | |
# source_gist("https://gist.github.com/4041561") |