Rich received an NSF CAREER Award in 2004 (for Meta Clustering), best paper awards in 2005 (with Alex Niculescu-Mizil), 2007 (with Daria Sorokina), and 2014 (with Todd Kulesza, Saleema Amershi, Danyel Fisher, and Denis Charles), co-chaired KDD in 2007 (with Xindong Wu), and serves as area chair for NIPS, ICML, and KDD.
The meta k-means algorithm then identifies cells that are co-clustered in more than 80% of k-means ++ runs and groups them into meta clusters initially.
These meta clusters are then iteratively merged, based on the similarity of their averaged, activity traces, to yield a variable, unspecified number of final clusters, of un-specified sizes.
Meta-analysis: Cluster meta-analysis was undertaken with three large studies with sufficient homogeneity in age categorisations and process indicators [ 7, 10, 22].
Surveying the landscape of cleantech clustering and meta-clustering, before focusing in depth on one case study, the contribution of clustering to transitioning towards a transformed green economy is considered.
However, the main confusions for meta-cluster I were with clusters III and IV, suggesting that labelling it as "Energetic" may have been premature (see Table 4).
As mentioned in Section 2.1, the poor classification accuracy of meta-cluster I is understandable, since that cluster contained the largest number of tags and was also considered to contain the weakest links between the tags (see Figure 1).
However, although these semantic structures could be distinguished sufficiently by their acoustic profiles at the generic, meta-cluster level; this was not the case at the level of the 19 individual clusters.
It resulted in five meta-clusters, shown in the lower section of stripes in Figure 1.
Even then, however, some of the meta-clusters were not adequately discriminated by their acoustical properties.
MDA is the Mean Decrease Accuracy in classification of the five meta-clusters by the acoustic features using RF.
