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We’ve seen how distances can be used in machine learning and data mining for different types of data, but we don’t only look at data in these areas. Remember in part one we looked at traditional, numerical distances that match our intuitions about distances and in part two we look…

Distances in Machine Learning (Pt. 2 – String Distances)

Big Data, Data Mining, Machine Learning

0

Distances are used throughout machine learning to help us (and our algorithms) figure out many things such as how far apart two instances are or how far our prediction is from the ground truth. The first part of this series looked at traditional distances that line up with our every…

Distances in Machine Learning (Pt.1 – Traditional Distances)

Big Data, Data Mining, Machine Learning

2

While you were reading about machine learning or developing your own algorithms, you may have come across the term distance. This is natural, since we often want to know how far apart two things are: instances that are very close together in our representational space are probably in the same…

Clustering in the Presence of Concept Drift

Big Data, Data Analysis

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Not all types of unsupervised learning algorithms have the same level of performance in dynamic environments. Algorithms with certain characteristics are more robust to changes in the data being produced.

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Distances in Machine Learning (Pt. 3 – Model Distances)

Distances in Machine Learning (Pt. 2 – String Distances)

Distances in Machine Learning (Pt.1 – Traditional Distances)

Clustering in the Presence of Concept Drift

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