Category Archives: Feature extraction

In the last two posts, I described how we could generalize the notion of “tokens” that we first saw when analyzing non-numeric census data, to time series. In this context, a token is a short snippet from a time series … Continue reading →

In the last post, I explained how to measure how similar two time series of the same length are using the idea of resonance from physics. The answer boiled down to calculating the dot product of the two time series, … Continue reading →

In the last few posts, I described how to turn data sets with varying amounts of structure into vector data that could be analyzed using standard data mining/machine learning algorithms. All the types of data that I looked at were … Continue reading →

In the past two posts, I’ve been looking at ways to turn “unstructured” data into vector data that can be analyzed with techniques like the ones that I’ve described elsewhere on this blog. One of the most common types of … Continue reading →

In last week’s post, I presented a brief tutorial on loading and analyzing the classic IRIS data set, which consists of four length measurements from each of 150 iris flowers. That data set was relatively easy to deal with because … Continue reading →

Since the start of this blog, we’ve covered a lot of different algorithms that attempt to discover and summarize the geometric structure in a given data set. But as it turns out, this part of the data analysis is the … Continue reading →