rwalk

#  This gist solves the hard-margin SVM problem in three ways: using quadprog, using kernlab's ipop, and by 
#  the e1071 wrapper around libsvm.
#
#  author: R. Walker  (r_walker@zoho.com)
#  LICENSE: MIT
library("quadprog")
library("kernlab")
library("e1071")

# Use Fisher iris data and binarize one of the species

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library(quadprog)
library(osqp)

# This gist compares the quadprog solver against OSPQ on a very simple problem.

##
##  The following example comes directly from `?? quadprog` documentation`
##
## Assume we want to minimize: -(0 5 0) %*% b + 1/2 b^T b
## under the constraints:      A^T b >= b0

rwalk

#  This gist compares three methods for solving a randomly generated quadratic program in R.
#  author: R. Walker  (r_walker@zoho.com)
#  LICENSE: MIT
library(quadprog)
library(kernlab)
library(ipoptr)
library(ggplot2)
library(reshape2)
#########################################################
# Random QP Generation (in the style of quadprog)

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library(foreign)
library(car)
library(ggplot2)
library(scales)

# load the CHIS data
file <- "~/projects/CHIS/chis15_adult_stata/Data/ADULT.dta"  # your file
CHIS   <- read.dta(file, convert.factors = TRUE)

# Recode insurance type

rwalk

#  This gist samples positive and negative examples of a topic 
#  in the Reuters21578 corpus using R's "tm" package to manage
#  the data.  After some simple transformations to the text,
#  the data are extracted to a document-term matrix and a simple
#  SVM model is fit to classify positive examples of the topic.
#
#  author: R. Walker  (r_walker@zoho.com)
#  LICENSE: MIT
#
# NOTE: Download the full Reuters21578 corpus from

rwalk

#!/usr/bin/python3
'''
Sample from the twitter API and post results to a file or to Kafka.
To use, set credientials as enviornment variables, e.g.
export TWITTER_ACCESS_TOKEN=... 
or source myfile
where myfile exports the authorization variables 
'''
import twython, json, re, argparse, subprocess, os, sys, time
from socket import timeout

rwalk

#!/usr/bin/python3
'''
Put documents from the stream into Kafka
'''
import argparse
from kafka import SimpleProducer, KafkaClient
from time import sleep

def chunk_iterable(A,n):
    '''An iterable that contains the iterates of A divided into lists of size n.

rwalk

#
#   Docker demo: container for a simple autocomplete program
#   Autocomplete script is python3 and consumes a dictionary
#   file packaged in the ubuntu operating system.
#

# start with the base ubuntu image
FROM ubuntu

# Tell apt-get that we are going to be NONINTERACTIVE

rwalk

#!/usr/bin/python3
'''
Autocompletion using a trie and a user supplied language file.
HINT: Linux/Unix users can look in "/usr/share/dict" for language files.

Author: rwalker
Email: r_walker@zoho.com
License: MIT
'''
import argparse, os, sys

rwalk

#  This gist compares three methods for solving a quadratic program in R.
#  The original problem is from the MathWorks MATLAB demo at:
#  http://www.mathworks.com/help/optim/examples/large-scale-bound-constrained-quadratic-programming.html
#
#  More information on this problem at:
#  http://quantitate.blogspot.com/2014/04/the-circus-tent-problem-with-rs-quadprog.html
#
#  author: R. Walker  (r_walker@zoho.com)
#  LICENSE: MIT
library(quadprog)