Clump represents a new approach to clustering and
classification. Traditional clustering
approaches\cite{KMeans,BallTrees,KDTrees,CoverTrees} cluster on
independent attributes, while Clump clusters on dependant
attributes. Clump also creates a maintainable rule tree. This rule
tree allows for human interaction both during the testing and training
phases of the algorithm.

\subsection{Human Interaction}
We plan on extending the functionality of Clump by introducing the
human element. During the training phase, we propose that humans be
presented with the possible patches at each node of the tree, and
choose which patch best addresses the data. Several variations on this
can be investigated. It may be best to show the user a subset of the
training data at the node, and allow the user to choose which rule is
``best'' free hand. Another possibility would be to present the user
with the top $X$ rules ordered randomly, as determined by the current
scoring algorithm described in \tion{scoring}. When presented with the
new rules, the user could be shown the score of each rule, the rule's
score's rank, or be shown no information about the score at all. By
allowing the human to interact with the rule tree, the knowledge of
domain experts can be exploited. Another alternative to this model
would be to only query the domain expert when the score between the
top rule candidates is similar enough to be ambiguous.

\subsection{Interface Options}
We expect to also expand Clump with a GUI, making it no longer just
command line based. A side effect of this move will make gathering user
feedback easier and more user friendly. An alternative would be
integrating Clump with the WEKA framework.

\subsection{Rule Creation}
Internally, Clump uses a custom algorithm to score the possible
rules. We plan to explore alternative rule scoring algorithms,
examining them for increased performance. Rules that test more than
one attribute are of great interest. These conjunctions of rules could
isolate clusters of information faster than singleton rules alone.
