Feature Overview ================ Markov Logic Networks in Python ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ * Inference (posterior marginal probabilties of formulas) * MC-SAT * Gibbs Sampling * Enumeration-Ask (exact) * Probabilistic Inference with Uncertain Evidence (Soft Evidential Update) * MC-SAT-PC * IPFP-M (iterative proportional fitting) * Inference (most probable explanation) * MaxWalkSAT (approximate) * WCSP (exact) * Learning * maximum pseudo-likelihood * maximum likelihood * Knowledge Representation * Fuzzy-MLN reasoning * Cardinality restrictions (count constraints) * Constraints on (prior) marginal probabilities of formulas * Constraints on posterior probabilities of ground atoms and formulas (soft evidence) * Evaluation * Tools for automated `k`-fold crossvalidation * Computation of confusion matrices with Latex export