Method and apparatus for quantum clustering
First Claim
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1. A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprising:
- (a) spanning a space, represented by a plurality of points;
(b) determining a density function over said space;
(c) associating a potential to said density function, such that said density function corresponds to an eigenstate of an operator which includes the potential;
(d) locating a plurality of local minima of said potential by evaluating, using a data processor, said potential in a plurality of evaluation points, thereby providing a plurality of potential values, and selecting minimal values of said potential values; and
(e) for each of said plurality of local minima, attributing at least one of said points;
thereby determining clusters of data within the dataset.
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Abstract
A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprises (a) spanning a space, represented by a plurality of points; (b) determining a density function over the space;(c) associating a potential to the density function; (d) locating a plurality of local minima of the potential; and (e) for each of the plurality of local minima, attributing at least one of the points; thereby determining clusters of data within the dataset.
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Citations
53 Claims
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1. A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprising:
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(a) spanning a space, represented by a plurality of points; (b) determining a density function over said space; (c) associating a potential to said density function, such that said density function corresponds to an eigenstate of an operator which includes the potential; (d) locating a plurality of local minima of said potential by evaluating, using a data processor, said potential in a plurality of evaluation points, thereby providing a plurality of potential values, and selecting minimal values of said potential values; and (e) for each of said plurality of local minima, attributing at least one of said points;
thereby determining clusters of data within the dataset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40)
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41. A method of determining clusters of biological data within a dataset, the dataset is represented by a multidimensional dataset-matrix, M, the method comprising:
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truncating the dataset-matrix, M, so as to construct a truncated space having a reduced dimensionality, said truncated space is represented by a plurality of points, each representing one biological entry; and using a data processor for partitioning said plurality of points, into a plurality of clusters; thereby determining clusters of determining clusters of biological data within the dataset. - View Dependent Claims (42, 43, 44, 45, 46, 47, 48, 49, 50)
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51. A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprising:
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(a) spanning a space, represented by a plurality of points; (b) determining a density function over said space by assigning a set of kernels, one for each of said plurality of points and summing over said set of kernels; (c) associating a potential to said density function; (d) using a data processor for locating a plurality of local minima of said potential; and (e) for each of said plurality of local minima, attributing at least one of said points; thereby determining clusters of data within the dataset.
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52. A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprising:
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(a) spanning a space, represented by a plurality of points; (b) determining a density function over said space; (c) associating a potential to said density function by determining an operator in manner that said density function is an eigenfunction of said operator with an eigenvalue, E, said operator includes said potential; (d) using a data processor for locating a plurality of local minima of said potential; and (e) for each of said plurality of local minima, attributing at least one of said points; thereby determining clusters of data within the dataset.
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53. A method of determining clusters of data within a dataset, the dataset is represented by a plurality of multidimensional data entries, the method comprising:
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(a) spanning a space, represented by a plurality of points, by eliminating at least one dimension from the dataset; (b) determining a density function over said space; (c) associating a potential to said density function; (d) using a data processor for locating a plurality of local minima of said potential; and (e) for each of said plurality of local minima, attributing at least one of said points; thereby determining clusters of data within the dataset.
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Specification