  In a series of papers by Dai and colleagues [1,2], a feature map (or kernel)
was introduced for semi- and unsupervised learning. This feature map is build
from the output of an ensemble of classifiers trained without using the
ground-truth class labels. In this critique, we analyze the latest version of
this series of papers, which is called Ensemble Projections [2]. We show that
the results reported in [2] were not well conducted, and that Ensemble
Projections performs poorly for semi-supervised learning.
