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Dear supporters I would like to know which algorithm should i used for my high-dimensional dataset ( 128 / 82 dimensions ) with string attributes matrix , entries are values for tf-idf , so which algorithm can work and clustering my instances that has 128 in one dataset and second dataset is 82 dimensions ) that are mention suitable algorithm for clustering high-dimensional dataset . Note : these dimension has been produced after string to word conversion, and attributes selection process , so result attributes has one class labels consist of 10 labels, would like to cluster it into clusters and validate result by cross validation process
AHC seems suitable for your analysis.
However, in case of a large dataset, you can perform the k-means clustering followed by ACH as described in the linked page below:
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