Bagging (bootstrap aggregating) is usually used with supervised methods to improve their stability and accuracy. The idea is to bootstrap the sample, build a predictive model on each bootstrapped sample and then combine the results to produce for classification a vote on the predicted class and for the continuous case an average prediction. If we bootstrap sample our data and build a separate hierarchical clustering solution on each sample can we then combine the results to produce a more stable clustering solution. … Bagging Hierarchical Clustering