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Data Mining

Data Mining
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Data Mining

Product Description

What topics will you cover?:-

  • What is data mining?
  • Where can it be applied?
  • How do simple classification algorithms work?
  • What are their strengths and weaknesses?
  • In what ways are real-life classification methods more complex?
  • How should you evaluate a classifier’s performance?
  • What is “overfitting” and how can you combat it?
  • How can ensemble techniques combine the result of different algorithms?
  • What ethical considerations arise when mining data?

By the end of the book, you'll be able to...

  • Demonstrate use of Weka for key data mining tasks
  • Evaluate the performance of a classifier on new, unseen, instances
  • Explain how data miners can unwittingly overestimate the performance of their system
  • Identify learning methods that are based on different flavors of simplicity
  • Apply many different learning methods to a dataset of your choice
  • Interpret the output produced by classification methods
  • Describe the principles behind many modern machine learning methods
  • Compare the decision boundaries produced by different classification algorithms
  • Debate ethical issues raised by mining personal data
¥450,000
¥480,000
Ex Tax: ¥450,000
  • Series: CS-0002
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