Published in Sydney's Child, August 2003 Many of us have mixed feelings when we think of studying Shakespeare at school. Such recollections can range from the depths of boredom and anguish to the heights of sublime joy and intellectual awakening. But regardless of our opinion of Shakespeare, we speak his language everyday. It is estimated that Shakespeare added around 1500 new words to the English language. Whenever we use our mind’s eye, to find method in someone’s madness, as they eat us out of house and home, because we thought they had a heart of gold and a spotless reputation but we were actually living in a fool's paradise; whenever we decide that discretion is the better part of valour or detect something in the wind; whenever we remark that brevity is the soul of wit, that love is blind or caution someone that all that glistens is not gold or advise someone to be neither a lender nor a borrower; from the salad days of youth, throu...
K means Clustering is one of the simplest and most commonly used unsupervised clustering algorithms around. The general approach is as follows: Choose k centroids randomly. Calculate the distance from each point in the dataset to be classified to each centroid. Assign each point to the nearest centroid. Calculate the centroids of the resulting clusters. Repeat until the centroids don't move too much. Here is some R code which generates a data set and implements the algorithm. Click here to see the animation. ########################################### # R code to implement k means classification ########################################## # NB - to make the animation - make sure you have ImageMajick installed from http://www.imagemagick.org/ ########################################## # initiate libraries library ( animation ) # set working directory setwd ( 'C:/Users/RF186004/Desktop' ) ######################################### ...
Go to http://www.datamilk.com/survey/ to have your say. Technology has made it easier than ever for people to collect and store a valuable trove of personal information about themselves. However, there is no readily available means by which individuals can reap a financial benefit by selling their personally generated data. Companies such as Facebook, Linkedin and Twitter are multi-billion dollar companies built almost entirely on user-generated data, so it’s clear that when used correct, your personal data is extremely valuable. There is a growing unease about the disparity between the value that companies realize from personal data and the financial rewards individuals gleam from this information. Prof. Tim Wu from Columbia Law School recently argued that Facebook should pay us for our posts. Individually your data may not be worth very much. but collectibely it is a goldmine. The problem is that there is currently no way for individuals to collect and moneti...
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