SCIENCE

SAND Technology has announced the introduction of support for the PMML (Predictive Model Markup Language) standard for statistical and data mining models in its industry-leading SAND CDBMS column-oriented, tokenized, bit-vector database. This new feature extends the power of SAND CDBMS to handle Extreme Data volume, variety, and velocity.

• Association Rules, including recommendation, exclusiveRecommendation, ruleAssociation
• Clustering Model, with support for center-based and distribution-based models, and all kinds of distances: euclidean, squaredEuclidean, chebychev, cityBlock, minkowski, simpleMatching, jaccard ,tanimoto, binarySimilarity.
• Regression Model, including linearRegression, stepwisePolynomialRegression, logisticRegression
• Neural Network Model, which supports activation functions such as: threshold, logistic, tanh, identity, exponential, reciprocal, square, Gauss, sine, cosine, Elliott, arctan
• Naïve Bayes
• Support Vector Machine, including Kernel Types: LinearKernelType, PolynomialKernelType, RadialBasisKernelType, SigmoidKernelType
• Ruleset Model
• Tree Model
• Functions: Normalization, Discretization, Mapping Values, Aggregation, User Defined Functions, Some elements of MathML, Matrix Operations, and the following built-in functions: +, -, *. /. and, min, max, sum, avg, log 10, ln, sqrt, abs, exp, pow, threshold, floor, ceil, round, isMissing, isNotMissing, equal, notEqual, lessThan, greaterThan, lessOrEqual, greaterThan, greaterOrequal, isIn, isNotIn, and, or, not, isIn, isNotIn, if, uppercase, substring, trimBlanks.

“SAND powers Extreme Data and our customers want to be able to fully leverage the power of SAND CDBMS for their data mining activities,” said Mike Pilcher, SAND’s Chief Operating Officer. “PMML gives them an easy, standards-based way to bring those models into SAND, quickly and with minimal effort, and to execute on them in a way that no other technology allows.”

“SAND CDBMS support for the PMML standard is a continuation of our analytic database vision,” said Richard Grondin, SAND’s Chief Technology Officer. “We are pleased to deliver this new functionality, which enables analytics on Extreme Data with even greater flexibility. Complex mathematical and statistical models, creating of advanced User Defined Functions, eliminating extraction requirements, and the ability to execute analytics directly on the data are just some of the benefits our customers are seeing thanks to SAND’s industry leading PMML support.”