1. A processor-implemented method of linear unsupervised classification allowing a database composed of objects and of descriptors to be structured, which is stable on the order of the objects, comprising: an initial step for transformation of the qualitative, quantitative or textual data into presence-absence binary data, wherein said processor-implemented method further comprises the following steps: determining a structural threshold α s function of the n 2 agreements between the objects to be classified, the structural threshold defining an optimization criterion adapted to the data, using the descriptors as structuring and construction generators of a partition or set of classes, regrouping of the classes of a partition over several hierarchical levels, said regrouping including the following steps: decreasing at each level the value of the structural threshold in such a manner that the negative contributions become positive, maximizing links between the classes formed where the links are determined by using the contribution from a pair of objects Lien ⁡ ( C q , C q ′ ) = ∑ i ∈ Cq ⁢ ∑ i ′ ∈ Cq ′ ⁢ Contrib ii ′ = ∑ i ∈ Cq ⁢ ∑ i ′ ∈ Cq ′ ⁢ C ii ′ - α ′ × f ⁡ ( C ii , C i ′ ⁢ i ′ ) with α′ the new value of α, combining two classes whose link is positive, and reiterate this process over all the levels, progressively merging a class generated by a descriptor and a partition, and for an optimization criterion involving a function ƒ(C ii ,C i′i′ )=Min(C ii ,C i′i′ ), linearizing sums of Minimum functions.