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Index

(A full index to the course appears at the end of Week 1.) Topic   Step Datasets Breast-cancer 5.2, 5.3, 5.4, 5.5, 5.11, 5.13   Credit-g 5.2, 5.3, 5.4, 5.5, …

Index

(A full index to the course appears at the end of Week 1.) Topic   Step Datasets Breast-cancer 4.14   Credit-g 4.13, 4.15, 4.16   Diabetes 4.4   Glass 4.2, …

Index

(A full index to the course appears at the end of Week 1.) Topic   Step Datasets Breast-cancer 3.8, 3.19   Contact-lenses 3.5   Credit-g 3.8, 3.19   Diabetes 3.7, …

Index

(A full index to the course appears at the end of Week 1.) Topic   Step Datasets Diabetes 2.7   Glass 2.7   Ionosphere 2.2, 2.3, 2.5, 2.7   Iris …

Index

At the end of each week is an index of topics covered that week. A full index to the course appears under DOWNLOADS, below. Topic   Step Datasets Breast-cancer 1.12 …

Farewell

Thanks for taking this course. We hope you’ve enjoyed it. This course has extended your knowledge and experience of practical data mining, following on from Data Mining with Weka. We’ve …

Summary

There’s no magic in data mining – no universal “best” method. It’s an experimental science. This video reviews what this course has covered, and points out many things that it …

ARFF and XRFF

Remember the ARFF format? – we’ve been using it all along. But it’s more powerful than you have seen. For example, it can encode sparse data, which often greatly reduces …

Performance optimization

Machine learning methods often involve several parameters, which should be optimized for best performance. Optimizing them manually is tedious, and also dangerous, because you risk overfitting the data (unless you …

Learning curves

How much data do you need? There is no easy answer; it depends on many features of the problem and dataset. One way to estimate it is to plot a …

The deep learning renaissance

In the last couple of videos I’ve been a bit negative about perceptrons and multilayer perceptrons – and the preceding quiz hasn’t exactly made a good case for them! But …

Performance of the multilayer perceptron

Let’s review the performance of multilayer perceptrons in the preceding quiz. First, 2 hidden layers never significantly outperform 1 hidden layer. Ignoring significance: 2 hidden layers are best for 1 …

Multilayer perceptrons

Multilayer perceptrons are networks of perceptrons, networks of linear classifiers. In fact, they can implement arbitrary decision boundaries using “hidden layers”. Weka has a graphical interface that lets you create …