Since the hardness results of Theorems 1 and 3 are stated for the two-classes case, we shall use the notation for some arbitrary rule , where is the value for class ``-'' and is the value for class ``+''. A positive value for means that is in favor of class ``+'' whereas a negative value gives a in favor of class ``-''. Value for gives a neutral with respect to the classes. We use a reduction from the -Hard problem ``Minimum Cover'' [Garey Johnson1979]:

**Name**: ``Minimum Cover''.**Instance**: A collection of subsets of a finite set . A positive integer , .**Question**: Does contain a cover of size at most , that is, a subset with , such that any element of belongs to at least one member of ?

Let denote the element of , and the element of . We define a set of Boolean variables in one to one correspondence with the elements of , which we use to describe the examples of . The corresponding set of literals is denoted . The sample contains two disjoint subsets : the set of positive examples , and the set of negative ones . contains examples, denoted by . We construct each positive example so that it encodes the membership of the corresponding element of in the elements of . More precisely,

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contains a single negative example, defined by:

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Suppose there exists a cover of satisfying . We create a decision committee consisting of monomials, each with one literal only and associated to a positive . Each monomial codes one of the sets in . The default class is ``-''. This decision committee is consistent with the examples of , otherwise some element of would not be covered. If there are only two values authorized for the vectors and they are , we simply create a DC consisting of one monomial with negative literals associated to a negative (the value for the negative class is greater than the one of the positive class); each of the negative literals codes one of the sets in . The default class is ``+''.

Suppose now that there exists a decision committee with at most literals consistent with . Denote each monomial of , in no specific order, and their associated values for . The monomials of can belong to three types of subsets of monomials:

- monotonous monomials (without negative literals),
- monomials containing only negative literals,
- monomials containing positive and negative literals.

We now treat independently two cases, depending on whether the default class of is ``+'' or ``-''.

- The default class is ``-''. Any positive example satisfies therefore a monomial in . There can exist two types of positive examples: those satisfying at least one rule of class I, and those not satisfying any class I rule (therefore satisfying at least one rule of class III). satisfies all class III and IV rules. Therefore,

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This shows that, if a positive example not satisfying any class I rules would satisfy all class IV rules, then it would be misclassified, which is impossible by the consistency hypothesis. This gives an important property, namely that any positive example not satisfying any class I rule cannot satisfy all class IV rules. Let us call**P**this property in what follows. We now show how to build a valid solution to ``Minimum Cover'' with at most elements. For any positive example ,- if satisfies at least one class I rule, choose in a subset of corresponding to a positive literal of some satisfied class I rule. This subset contains .
- if does not satisfy any class I rule, there exists from
**P**some class IV rule which is not satisfied. Among all negative literals of a class IV rule which is not satisfied by , choose one which is positive in (causing it not to satisfy the rule), and then choose the corresponding element of . This subset of contains .

- The default class is ``+''. satisfies all class III and IV rules. Therefore,

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Even if the inequality is now strict, it gives the same procedure for efficiently building the solution to ``Minimum Cover'' with at most elements, by using the same argument as in the preceeding case.