To use these functions, the Probabilistic Feature is required.
The probabilistic feature provides arbitrary functions to work with discrete and continuous random variables in a data stream and provides algebraic operator (+, *, -, /) to perform probabilistic addition, subtraction, multiplication, division, and exponentiation.
Estimates the multivariate normal distribution probability with lower and upper integration limit.
Converts the two object into a 2D vector.
Similar to the as2DVector function, this function creates a 3D vector with the given objects.
Calculates the Bhattacharyya distance between two distributions.
SELECT similarity(as2DVector(x1,y1), as2DVector(x2,y2)) FROM stream |
Calculates the Mahalanobis distance between the distribution and the value. The value can be a scalar value or a vector.
SELECT distance(as3DVector(x, y, z), [1.0;2.0;3.0]) FROM stream |
Calculates the Kullback-Leibler divergence of the two given probability distributions.
SELECT kl(as3DVector(x, y, z), as3DVector(a, b, c)) FROM stream |
Calculates the log Likelihood between the given points and the probability distribution.
SELECT loglikelihood([1.0;2.0;3.0], x) FROM stream |