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Missing Inaction Can Be Hazardous to Your Data Mining Project
By Tim Graettinger
Did anyone ever tell you that you have "dirty data"? Were you offended? Surprised? Did you vow to do something about it? Or did you just resign yourself to living with it?
Missing data is one common component that contributes to the unpleasant moniker, dirty data. In this installment of my series on the nuts and bolts of data mining,
we'll tackle missing data. We'll start first with detecting it. From there, we'll diagnose the issues, both qualitatively and quantitatively.
With a proper diagnosis, we can then prescribe a treatment for any of the variety of situations that crop up. You'll walk away with a mental framework and a set of
tools and techniques that are invaluable for real-world data mining applications. Read the article.
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If only I knew...
By Tim Graettinger
If only I knew:
- who will renew their service plan
- who will defect to the competition
- who will buy our new product
- who will become a high-value customer
Sound familiar? To make better decisions as business people, we all wish we could see into the future and deep into the hearts and minds of our customers. In response to the wishes above, this article asks the question,
"Suppose I knew, what would I do?" We will describe the process to translate the wish for customer knowledge into actionable strategies and tactics.
Read the article.
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Grab Bag: Frequently-Asked Data Mining Questions and Answers
By Tim Graettinger
For the past year, I have presented a data mining "nuts and bolts" session during a monthly webinar. My favorite part is the question-and-answer portion at the end. Participants with a diverse range of interests and experience toss out a lot of great questions. In this article, I'd like to share with you some of the best-of-the-best of those interactions. Some responses include pointers to other sources that I hope you'll find instructive and useful. Without further ado, let's get to the questions.
Read the article.
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