Initial commit of some distance metrics and initial kNN code
Updated kNN to use Beam instead of BoundedPriorityQueue. Removed BPQ
Moved all implicit DMs to own object
Updated kNN with corrected Ordering for Beam and added distance function to retrieve closest points with distances
Updated DataMatrix to handle labels of any type. Also switched from Seq to DenseVector for feature representation
Very minor changes updating documentation and importing scala.util.Random
*Added Iris dataset. \n*Added test harness for Nearest Neighbor using Leave-One-Out CV with code in Datasets object. \n\tMight be old, should probably refactor LOOCV into more standardized framework for testing. \n*Added test for kNN based on Iris dataset.
Updated DMImplicits with type values to make reference in kNN code easier. Modified kNNTest to use this
Merge branch 'feature/kNN' into devel

* Merge represents completed kNN code with test. Includes addition of Iris dataset.

* feature/kNN:
  Updated DMImplicits with type values to make reference in kNN code easier. Modified kNNTest to use this
  *Added Iris dataset. \n*Added test harness for Nearest Neighbor using Leave-One-Out CV with code in Datasets object. \n\tMight be old, should probably refactor LOOCV into more standardized framework for testing. \n*Added test for kNN based on Iris dataset.
  Very minor changes updating documentation and importing scala.util.Random
  Updated DataMatrix to handle labels of any type. Also switched from Seq to DenseVector for feature representation
  Updated kNN with corrected Ordering for Beam and added distance function to retrieve closest points with distances
  Moved all implicit DMs to own object
  Updated kNN to use Beam instead of BoundedPriorityQueue. Removed BPQ
  Initial commit of some distance metrics and initial kNN code