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Data mining is such a broad topic and covers many different approaches like cluster analysis, classification, association, and cause/effect modeling. Within each of these approaches are many different techniques. For this assignment, you assume the role of the teacher and provide a brief educational presentation on one of the following classification topics not covered in detail in the text:
- Logistic Regression
- Decision Trees
- The Naïve Bayes Classifier
- Support Vector Machines (SVMs)
- Neural Networks
At a minimum, you should define/describe the classification technique, explain how it is useful in the business world, and provide an example scenario where it can be used (preferably where you work).
Alternatively, you may instead compare two different approaches in your presentation. For example, you might consider comparing and contrasting Logisitic Regression and SVMs, etc.
Answer these separately –
- understand the purpose of conducting data mining on a data set
- Develop ideas of how data mining could be used in your place of employment
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