Question: Algorithm for clustering and visualization of non-normalized time-series data
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3.1 years ago by
sevenless20 wrote:

I am looking for an algorithm, preferably implemented in R, that I can use to cluster non-normalized time-series data. My data set consists of scores that change over time which is why I want to keep the original values and avoid normalization. A very useful additional feature would be the visualization of the clustered time-series scores plotted together with their respective centroid.

I would be very grateful for any suggestions!

clustering time-series data R • 888 views
ADD COMMENTlink modified 3.1 years ago by Jean-Karim Heriche24k • written 3.1 years ago by sevenless20
gravatar for Jean-Karim Heriche
3.1 years ago by
EMBL Heidelberg, Germany
Jean-Karim Heriche24k wrote:

You can compute a matrix of distances between time series using dynamic time warping. Different variants of dynamic time warping are implemented in the R package dtw. You can then use the distance matrix with many clustering algorithms that accept a distance or similarity matrix as input. For visualization, you can use the distance matrix as input for multidimensional scaling (function cmdscale() or isoMDS() in the MASS package or layout.mds() in the igraph package).

ADD COMMENTlink written 3.1 years ago by Jean-Karim Heriche24k
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