Data Mining Introduction - Part 1
Data Mining Definition and Origins
If you are a beginner in data mining
and want to become at least familiar with the main concepts and
terminologies, maybe the first step would be to acquire a clear
bird's eye view about the whole domain - definition, inception,
classification, influences, trends - but without diving into too deep
and scholastic details. And, of course, you do that by searching on
Internet and skimming whatever books you have at hand. You might say
that one day would be more than enough to get an overall understanding
about this domain. But you don't have a clue about the trouble you're
getting into. These are some of the questions that I'm sure you'll
start asking yourself: How is data mining related to predictive
analysis? How is it related to knowledge discovery? What about data
mining vs machine learning and artificial intelligence? What is the
difference between predictive/descriptive and supervized/unsupervized?
Can we compare these 2 classifications first of all? And this is just
the beginning...
This article wants to shed some light on this questions and present all
these concepts in a very simple manner. Read on.
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Data Mining Introduction - Part 2
Data Mining Techniques
Classifying data mining concepts has been allways a sensitive subject in data mining. There are dozens of classifications of data mining with classes,
sub-classes and sub-sub-classes. And sometimes a particular class may have dozens of names. So I'll never brag about being able to
draw the complete picture. Read more.
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Data Mining Introduction - Part 3
Mining Frequent Patterns (Maximal and Closed Frequent Itemsets)
Mining frequent patterns is probably one of the most important concepts in data mining. A lot of other data mining tasks and theories stem from
this concept. It should be the beginning of any data mining technical training because, on one hand, it gives a very well shaped idea about what data mining is and,
on the other, it is not extremely technical. In this article we'll talk only about frequent patterns and specifically, about frequent itemsets.
Read more.
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Data Mining Introduction - Part 4
Association Rules
I promiss I won't discuss here about the "beer and diapers" story. I'll just talk about what a basic association rule is
and lay down the fundation for the methodes and algoritms used to find the associations. What is Association Rule mining? It is a way to find interesting associations among large sets of data items.
Read more.
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Data Mining Introduction - Part 5
Algorithms for Mining Frequent Itemsets
There are douzines of algorithms used to mine frequent itemsets. Some of them, very well known, started a whole new era in data mining. They made the concept of mining frequent itemsets and association rules possible. Others are variations that bring improvements mainly in terms of processing time. We'll go through some of the most important algorithms first briefly in this article, and then in more detail in the subsequent articles. The algorithms vary mainly in how the candidate itemsets are generated and how the supports for the candidate itemsets are counted.
Read more.
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