Method for stable and linear unsupervised classification upon the command on objects
First Claim
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 n2 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
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Abstract
A 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, comprises an initial step for transformation of the qualitative, quantitative or textual data into presence-absence binary data. A structural threshold αs function is determined of the n2 agreements between the objects to be classified with the structural threshold defining an optimization criterion adapted to the data. The descriptors are used as structuring and construction generators of a partition or set of classes. A class generated by a descriptor and a partition (40, 41, 42) progressively merged. For an optimization criterion involving a function ƒ(Cii,Ci′i′)=Min(Cii,Ci′i′), sums of Minimum functions are linearized.
1 Citation
7 Claims
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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:
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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 n2 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 - View Dependent Claims (2, 3)
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4. A device allowing linear unsupervised classification that allows 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, said device comprising at least the following elements:
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
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 n2 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 - View Dependent Claims (5)
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
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6. A device allowing linear unsupervised classification that allows a database composed of object 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, said device comprising at least the following elements:
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
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 n2 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
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
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7. A device allowing linear unsupervised classification that allows 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, said device comprising at least the following elements:
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
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 n2 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
- a computer comprising a memory, a database and a processor adapted to implement the following steps;
Specification