Time Series Clustering

TIME SERIES CLUSTERING

Time series clustering is to partition time series data into groups based on seriability or distance so that time series in the same cluster are similar.

For Time Series clustering with R the first time is  to work out an appropriate distance/similarity metric and then at the second step , use existing clustering techniques such as k-means hierarchial clustering , density based clustering or subspace clustering to find clustering structures.

Clustering is a solution for classifying enoromous data when there is not any early knowledge about classes, with emerging new concepts like cloud computing  and big data and their vast applications and research works have been increased on unsupervised solutions like clustering to extract knowledge from the data.

In case of huge data set , using supervised classification solutions is almost impossible , while clustering can solve this problem using un-supervised approaches.