tonicebrian

# =============
# Introduction
# =============
# I've been doing some data mining lately and specially looking into `Gradient
# Boosting Trees <http://en.wikipedia.org/wiki/Gradient_boosting>`_ since it is
# claimed that this is one of the techniques with best performance out of the
# box.  In order to have a better understanding of the technique I've reproduced
# the example of section *10.14.1 California Housing* in the book `The Elements of Statistical Learning <http://www-stat.stanford.edu/~tibs/ElemStatLearn/>`_.
# Each point of this dataset represents the house value of a property with some
# attributes of that house. You can get the data and the description of those

cyrus-and

#!/usr/bin/env bash
# usage: <command> | pastebin [+|++|+++]
#
# (none): paste expires in 10 minutes
# +:      paste expires in 1 hour
# ++:     paste expires in 1 day
# +++:    paste expires in 1 months

HOST='pastebin.com'

mxcl

#!/bin/sh
# Just copy and paste the lines below (all at once, it won't work line by line!)
# MAKE SURE YOU ARE HAPPY WITH WHAT IT DOES FIRST! THERE IS NO WARRANTY!

function abort {
  echo "$1"
  exit 1
}

set -e

bycpx

[diff "iworkpages"]
	textconv = xsltproc $GIT_DIR/Pages.xsl

defunkt

#!/bin/sh -e
#
# Usage: browser
#        pipe html to a browser
# e.g.
#  $ echo '<h1>hi mom!</h1>' | browser
#  $ ron -5 man/rip.5.ron | browser   

if [ -t 0 ]; then
  if [ -n "$1" ]; then

samstokes

if "[email protected]" =~ /@(.*)/
  $1
else
  raise "bad email"
end
# => "example.com"