1. A computer program product for outlier detection, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to, based, at least in part, on a set of CF-trees, identify a plurality of subsets of CF-trees included in the set of CF-trees; program instructions to initiate cluster feature (CF)-tree based hierarchical clustering on leaf entries of a plurality of CF-trees included in a given subset of CF-trees, wherein each CF-tree presents a respective set of local data as leaf entries; program instructions to generate respective partial clustering solutions using the given subset of CF-trees, wherein clustering activity for a resulting CF-tree ceases when a threshold number of sub-clusters has been reached, and wherein a partial clustering solution includes a set of regular sub-clusters that are included in the resulting CF-tree and candidate outlier sub-clusters that contain summaries of sets of data records; program instructions to generate initial regular clusters by performing hierarchical clustering using the set of regular sub-clusters; program instructions to determine, for each candidate outlier sub-cluster of a plurality of candidate outlier sub-clusters, a closest initial regular cluster, and a distance separating the respective candidate outlier sub-cluster and the respective closest initial regular cluster; and program instructions to determine which candidate outlier sub-clusters are outlier clusters based, at least in part, on which candidate outlier sub-clusters have a computed distance to their respective closest initial regular cluster that is greater than a corresponding distance threshold associated with their respective closest initial regular cluster.