2019 / Andreas Koenzen

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M.Sc. student at the University of Victoria in beautiful British Columbia.

M.Sc. UVic:

CSC 578D

Notes and examples taken during the course CSC578D (Data Mining) at the University of Victoria. The datasets used in each explanation can be found here. They belong to the Weka dataset and can be found also by downloading the Weka application here.

If you want to borrow some of this code for your own use is fine by me, BUT please write me an email first requesting permission, and add a mention as to the origin of the code you used.

  1. Decision Trees - ID3

    The ID3 algorithm is used for educational purposes nowadays, supports only nominal values.

  2. Rules-Based Classifier
  3. Naïve Bayes Classifier
  4. Naïve Bayes Classifier for Text
  5. Simple Linear Regression using scikit-learn
  6. Perceptron
  7. Linear Regression
  8. Logistic Regression
  9. Project (Crime Analysis in Chicago)
  10. Final Assignment (SVM, Clustering, Association Analysis, Recommendation Systems)

Random junk:

  1. Simple Bayes Problem

    I set up to develop this problem after listening to the "You Are Not So Smart" podcast, episode 73 "Bayes' Theorem". You can find the link to the podcast here.

  2. Compute Primes in C
  3. Integer to Byte Array in Java (Spanish)
  4. Algorithm for converting SAX to DOM.

Past Projects:

  1. Final Bachelor's Project (In Spanish)