(Top 30 coins)
Historical Data aquired from Crypto Compare ! .
Donate: BTC 16BghZgtoh9hmifLskv1Jtec46abQZ1Kp , FRC 1KQ4z7mRxLPhPAzcZTnUPCPHLC67B8h2Hr
number of coins for PCA :
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Cluster analysis seeks to identify groups in the dataset: data points that are close to each other and far from other groups. The top 30 crypto-currencies do not form well defined different groups. Rather they form one big group with fuzzy edges and outliers. To try to form meaningful groups we have done 2 things: (1) the 2-day average price change and average volume are used as the clustering variable; and,(2) PCA analysis is preformed on this data set to reduce the number or variables for clustering. Here, a hybrid k-means clustering with seeds found from isolating and preclustering outliers (just a fun hack because because there is a lack of good Javascript clustering libraries) is used to make 4 clusters based on the first 6 eigenvectors. For interesting results, the 2-day average price change is presented with the 2-day average volume In the 4 cluster results below, positive value are daily positive price change (ie slope of price curve). Please try a few iterations to find interesting clusters. Pumping coins appear in small outlier cluster of 2 to 4 coins and show an up-tick at the end of the time series. The cluster assignments can be found below in the appendix. Go back to the first chart to plot individual cluster members.
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