pasteur.extras.synth.privbayes.implementation

Description

Functions

add_multiple_to_pset(s, x, h)	Given parent set s, adds attributes x with heights h.
add_to_pset(s, x, h)	Given parent set s, adds attribute x with height h.
calc_entropy(mar)	Calculates the entropy for the provided data.
calc_mutual_info(j_mar, x_mar, p_mar)	Calculates mutual information I(X,P) for the provided data using log2.
calc_noisy_marginals(oracle, attrs, nodes, ...)	Calculates the marginals and adds laplacian noise with scale noise_scale.
calc_r_function(j_mar, x_mar, p_mar)	Calculates the R(X,P) function for the provided data.
find_maximal_parents(heights, domain, ...)
greedy_bayes(oracle, attrs, e1, e2, theta, ...)	Performs the greedy bayes algorithm for variable domain data.
print_tree(attrs, nodes, e1, e2, theta, t)
sample_rows(attrs, nodes, marginals, n)	rtype: DataFrame
sens_entropy(n)	Provides the sensitivity for the entropy function for a given dataset size (n).
sens_mutual_info(n)	Provides the the log2 sensitivity of the mutual information function for a given dataset size (n).
sens_r_function(n)	Provides the the R function sensitivity for a given dataset size (n).

Classes

Node(attr, col, domain, partial, p)