1. A method for the generation of a classification tree as a function of a classification model and from a set of data to be classified, described by a set of attributes, wherein the method comprises obtaining said classification model, itself comprising defining a mode of use for each attribute, which comprises specifying which property or properties are possessed by said attribute among the at least two following properties, which are not exclusive of each other: an attribute is marked target if it has to be explained; and an attribute is marked taboo if it has not to be used as an explanatory attribute, an attribute not marked taboo being an explanatory attribute; and wherein, said classification model belongs to the group comprising: supervised classification models with one target attribute, in each of which a single attribute is marked target and taboo, the attributes that are not marked target being not marked taboo; supervised classification models with several target attributes, in each of which at least two attributes, but not all the attributes, are marked target and taboo, the attributes not marked target being not marked taboo; and unsupervised classification models, in each of which all the attributes are marked target and at least one attribute is not marked taboo.