Clustering
Peter Hilbers
1 Introduction on machine learning techniques
In weeks 4 through 7 the emphasis is on a second biomedical data analysis method, viz. machine learning. Roughly stated machine learning techniques can be split into 2 parts:
• Supervised learning: As the name already suggests learning takes place in the presence of a supervisor(teacher) meaning that some data is already tagged with the correct answer. The labeled data, helps you to predict outcomes for unforeseen data.
• Unsupervised learning: In unsupervised learning the data is unlabeled.
A simple example to explain the difference is: If you see a chair in a furniture shop you have never seen before, you immediately know that it is a chair. No supervisor has to assist you in giving it that label, so you ’learned’ it unsupervised.
In another case when you are not sure what object it is, you may ask for help to a supervisor to tell you what kind of object it is, so you ask for the label, and then it becomes supervised.
The most used supervised method is classification. In classification, we have data points for which the groups are already known, and we analyze what differentiates these groups (i.e., a classification function) to properly classify future data.
A popular unsupervised method is clustering. In clustering, we consider data points for which groups are unknown and undefined, and we somehow divide them into groups as well as determine what differentiates the groups from each other.
In both methods objects(data points) are grouped such that objects in the same group are more similar to one another than they are to objects in other groups. Both in clustering and classification we have to define what it means that 2 data points (objects) are looking similar, hence when do they belong to the same group. To that end usually a distance is defined. In this notes therefore the topic of distances will be discussed (see section 4), but we start with two topics from computing science that are often used in machine learning, viz. recursion (see section 2) and graphs (see section 3).
A fundamental notion in programming is repetition. In previous courses and lectures iterative methods such as for and while-constructs have been introduced. Here we discuss another repetition technique, viz. recursion. Informally speaking recursion is a repetition method in which the object to be defined is used itself. That sounds maybe somewhat confusing so an example may help.
2 Recursion
A fundamental notion in programming is repetition. In previous courses and lectures iterative methods such as for and while-constructs have been introduced. Here we discuss another repetition technique, viz. recursion. Informally speaking recursion is a repetition method in which the object to be defined is used itself. That sounds maybe somewhat confusing so an example may help.
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