Entropy Functions

The entropy functions determine variance and probability density across a given distribution.

The URI for the data science functions is <http://cambridgesemantics.com/anzograph/statistics#>. For readability, the syntax for each function below includes the prefix stats:, defined as PREFIX stats: <http://cambridgesemantics.com/anzograph/statistics#>.

Cross Entropy (CROSSENTROPY)

The Cross-entropy function computes cross-entropy, which is commonly used to quantify the difference between two probability distributions.

Syntax

stats:crossentropy(p, q)  
Parameter Type Description
p double True probabilities for x.
q double Predicted probabilities for x.

Returns

Type Description
double The cross entropy value.

Discrete Entropy Metric (DISCENTROPY)

The Discrete entropy function calculates entropy for maps on finite sets, referred to as discrete entropy.

Syntax

stats:discentropy("data")
Parameter Type Description
data string Column data.

Returns

Type Description
double The discrete entropy value.

Differential Entropy or Continuous Entropy Metrics

Differential entropy (also referred to as continuous entropy) is entropy that can be computed for distributions with a continuous random variable.

The following functions produce entropy calculations. For details about the functions, see Distribution Functions.

  • Continuous Uniform Distribution (CONUNIDIST)
  • Discrete Uniform Distribution (DISCUNIDIST)
  • Exponential Distribution (EXPDIST)
  • Laplace Distribution (LAPLACEDIST)
  • Log Normal Distribution (LOGNORDIST)
  • Normal Distribution (NORMDIST)
  • Weibull Distribution (WEIBULDIST)