Struct ILPProblem 

pub struct ILPProblem {
    pub positive_examples: Vec<String>,
    pub negative_examples: Vec<String>,
    pub background: Vec<String>,
    pub target: String,
}

Represents a learning problem in Inductive Logic Programming. ILP learns logic programs (Horn clauses) from examples and background knowledge.

Fields

positive_examples: Vec<String>

Positive examples (facts that should be entailed).

negative_examples: Vec<String>

Negative examples (facts that should NOT be entailed).

background: Vec<String>

Background knowledge (predefined facts and rules).

target: String

Target predicate to learn.

Implementations

impl ILPProblem

pub fn new(target: &str) -> Self

Create a new ILP problem.

pub fn add_positive(&mut self, example: &str)

Add a positive example.

pub fn add_negative(&mut self, example: &str)

Add a negative example.

pub fn add_background(&mut self, fact: &str)

Add background knowledge.

pub fn total_examples(&self) -> usize

Count the total number of training examples.

pub fn accuracy(&self, hypothesis: &[String]) -> f64

Accuracy of a candidate hypothesis on this problem. The hypothesis is a list of clauses (strings). Simplified: count how many positive examples are in the hypothesis “model”.

Trait Implementations

impl Clone for ILPProblem

fn clone(&self) -> ILPProblem

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ILPProblem

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.