1. A method for clustering data or objects O i , O j taking the form of an array S, each of the elements of said array S corresponding to a value of similarity s ij existing between said objects O i , O j said method being implemented within a computer linked with a database containing the data or objects to be clustered comprising a work memory, and a processor, the method comprising: 1) determining a number k of classes of objects in the following manner: take an object O i which has the fewest possible similarities s ij with the other objects O j that is to say the one for which the sum of the components ∑ i ′ = 1 n s ii ′ of its profile is the smallest, Place the individual O i in a first class C 1 , Consider the remaining objects O j with O j different from O i and take from among them a second object O j , for which the sum of the components of its profile is the smallest out of the remaining objects, if the relationship l jC 1 computed between the new object O j with the previous class C 1 consisting of a single individual is negative, then create a new class C 2 and place the object O j in this new class, otherwise if this relationship is positive, place the object O j in the class C 1 , repeat until all the objects O j belong to a class of index k, on completion of this first step the method has a set of κ classes, 2) for each of the κ classes found in step 1), determine the value of the relationships between a class C k and the other classes C k′ such that k′ is different from k, if all the relationships determined l C k C k′ are negative, then do not merge the class C k with another class, Otherwise, merge the class considered C k with the class C k′ with which it has the strongest relationship, the highest value l C k C k′ , add this value to the criterion C ( X ) = ( ∑ k = 1 κ l C k C k ) + l C k C k ′ until stability of this criterion is obtained, on completion of step 2), the method has L classes with L≦κ, 3) determining, for each object O j of each class C l with l≦L one by one, the value of the relationship l iC m of this object with each of the classes C j other than the class of index k into which it was classed in the initial step, if the value of the relationship l iC m with the class of index m is greater than the value of the relationship l iC k then transfer the object from its class of index k to the new class of index m, this is continued until all the values of the relationships l iC k are negative.