About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

• Common Core:
  • Added checkedAdd and checkedMultiply functions to MathUtil, providing a means for conducting Integer addition and multiplication with explicit checking for overflow and underflow, and throwing an ArithmeticException if they occur. Java fails silently in integer over(under)flow situations.
  • Added explicit integer overflow checks to DenseMatrix. The underlying MTJ library stores dense matrices as a single dimensional arrays of integers, which in Java are 32-bit. When creating a matrix with numRows rows and numColumns columns, if numRows * numColumns is more than 2^31 - 1, a silent integer overflow would occur, resulting in later ArrayIndexOutOfBoundsExceptions when attempting to access matrix elements that didn't get allocated.
  • Added new methods to DiagonalMatrix interface for multiplying diagonal matrices together and for inverting a DiagonalMatrix.
  • Optimized operations on diagonal matrices in DiagonalMatrixMTJ.
  • Added checks to norm method in AbstractVectorSpace and DefaultInfiniteVector for power set to NaN, throwing an ArithmeticException if encountered.
• Learning Core:
  • Optimized matrix multiplies in LogisticRegression to avoid creating dense matrices unnecessarily and to reduce computation time using improved DiagonalMatrix interfaces.
  • Added regularization and explicit bias estimation to MultivariateLinearRegression.
  • Added ConvexReceiverOperatingCharacteristic, which computes the convex hull of the ROC.
  • Fixed rare corner-case bug in ReceiverOperatingCharacteristic and added optional trapezoidal AUC computation.
  • Cleaned up constant in MultivariateCumulativeDistributionFunction and added publication references.