Computational Methods in Systems Biology

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Probably Approximately Correct Learning 77

2.2 PAC Learning Algorithms


Valiant showed the learnability of some important classes of functions in this
framework, in particular for Boolean formulae in conjunctive normal forms with
at mostkliterals per conjunct (k-CNF), and for monotone (i.e. negation free,
positive literals only) Boolean formulae in disjunctive normal form (DNF).
The computational complexity of the PAC learning algorithms for these
classes of functions is expressed in terms of a functionL(h, S), defined as the
smallest integerisuch that iniindependent Bernoulli trials, each with probabil-
ity at leasth−^1 of success, the probability of having fewer thanSsuccesses is less
thanh−^1. Interestingly, this function isquasi-linear inhandS, more precisely
for all integersS≥1 and realsh>1, we haveL(h, S)≤ 2 h(S+ logeh)[ 24 ].


Theorem 1 ([ 24 ]).For anyk, the class ofk-CNF formulae onnvariables is
learnable with an algorithm that usesL(h,(2n)k+1)positive examples and no call
to the oracle.


The proof is constructive and relies on Algorithm 1 below. In this algorithm,
the initialization of the learned functiongto the false constraint expressed as
the conjunction of all possibleclauses (i.e. disjunctions of litterals) leads to
the learning of a minimal generalization of the positive examples with no false
positive and low probability of false negatives.


Algorithm 1.PAC-learning ofk-CNF formulae.



  1. initialisegto the conjunction of all the (2n)kpossible clauses of at mostkliterals,

  2. doL(h,(2n)k+1)times
    (a)v:=Sample()
    (b) delete all the clauses ingthat do not contain a literal true inv

  3. output:g


In our implementation of the PAC-learning algorithm fork-CNF formulae,
we shall make use of the lattice structure ofk-clauses ordered by implication.
Interestingly, this data structure allows for



  • O(1) access to anyk-clause;

  • and for a clausec,O(1) access to the smallest clauses implied bycand to the
    biggest clauses that implyc.


The class of monotone DNF formulae is also learnable. Let thedegreeof
a Boolean formula be the largest number of prime implicants (i.e., minimal
formulae covering one of the product-terms of the Boolean formula expressed as
a sum of products) in an equivalent rewriting of the formula as a non-redundant
sum of prime-implicants.

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