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E-Mail: redmond@lasalle.edu  

Chapter 1

Chapter 2

Chapter 3

Chapter 4, Section 4.1

Chapter 4, Section 4.2

Midterm from last time I taught this class. ( answers).

Chapter 4, Section 4.3 - ID3 - along with a spreadsheet for calculating entropy (right click to download)

Chapter 4, Section 4.4 - Prism

Chapter 4, Section 4.6 along with a basketball spreadsheet showing the use of linear regression and use of linear regression for a classification problem (right click to download) along with a bank spreadsheet showing the use of linear regression (right click to download)

Chapter 4, Section 4.7

Chapter 4, Section 4.8 along with a bank purely numeric data spreadsheet showing the use of K Means clustering (right click to download) along with a another version with a different random starting point showing how different results happen (right click to download)

Chapter 5 along with a spreadsheet showing doing a statistical T-test using Excel (right click to download) and a spreadsheet showing various error measures using Excel (right click to download)

To summarize key aspects of covered algorithms, I have created a table comparing them. This is available as PowerPoint '07 or Word '03 There's a bug with downloading '07 files - you may have to change the file name so that the extension is pptx (correct) instead of zip (why? - Bill Gates doesn't play well with other kids?)

Skeleton instructions for using Weka Experimenter Environment

Chapter 7 along with a spreadsheet showing calculations in support of Entropy based discretization (right click to download) and a spreadsheet showing calculations in support of greedy Entropy binning (right click to download)

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