Claims
- 1. A method for hierarchical visualization of multi-dimensional data, comprising:
(a) applying a first dimension-reduction process to a multi-dimensional data set to obtain a first visualization; (b) selecting a subset of the multi-dimensional data set associated with a selected region of the dimension-reduced first visualization where more detail is desired; and (c) applying a second dimension-reduction process to the selected subset of the multi-dimensional data set to obtain at least one additional visualization.
- 2. The method of claim 1, wherein (b) and (c) are repeated for a further subset associated with a subregion of the selected region.
- 3. The method of claim 1, wherein the subregion includes a mixed portion.
- 4. The method of claim 1, wherein (b) and (c) are repeated, until a dimension-reduced visualization having a desired level of separation of points is obtained.
- 5. The method of claim 4, wherein each visualization has an associated angle of view and a view of the multi-dimensional data set is obtained at an angle of view associated with the dimension-reduced visualization having the desired level of separation of points.
- 6. The method of claim 1, wherein each visualization has an associated angle of view and a view of the multi-dimensional data set is obtained at an angle of view associated with a selected one of the at least one additional visualization.
- 7. The method of claim 1, wherein the first visualization has a first angle of view, and the additional visualization has a second angle of view different from the first angle of view.
- 8. The method of claim 1, wherein the at least one additional visualization is at a higher level of detail than the first visualization.
- 9. The method of claim 1, wherein the second dimension-reduction process applies the same dimension-reduction technique as used in the first dimension-reduction process.
- 10. The method of claim 1, wherein the first dimension-reduction process and the second dimension-reduction process apply respectively different dimension-reduction techniques.
- 11. The method of claim 1, wherein the second dimension-reduction process includes applying a continuous dimension-reduction technique to obtain a sequence of dimension-reduced visualizations.
- 12. The method of claim 11 further comprising
selecting two data points in the multi-dimensional data set for distance estimation, wherein if the two data points appear to be far apart in any one of the dimension-reduced visualizations, the two data points are far apart in the original multi-dimensional space.
- 13. The method of claim 12, wherein the continuous dimension-reduction technique includes principal component analysis, and a largest one of the reduced-dimension distances is a lower bound estimate of an actual distance between the two selected data points in the original multi-dimensional space.
- 14. The method of claim 1 further comprising utilizing a hierarchical cluster tree to automate generation of hierarchical visualizations by generating a visualization for each node of the cluster tree.
- 15. The method of claim 1, wherein the subset selected in (b) corresponds to a mixed region.
- 16. The method of claim 1, wherein the multi-dimensional data set includes non-numeric data and is preprocessed into numerical form prior to dimension reduction.
- 17. The method of claim 1, wherein the additional visualization is consulted with data from a test set by applying a mapping corresponding to the second dimension-reduction process.
- 18. The method of claim 1, wherein the method is applied to classify the multi-dimensional data set according to one or more features associated with the data set.
- 19. The method of claim 1, wherein the multi-dimensional data set is collected from a production process, and the method is applied to obtain information for predicting product properties.
- 20. The method of claim 1, wherein the multi-dimensional data set corresponds to data collected from a system, and the method is applied to obtain information for diagnosing a problem in the system.
- 21. The method of claim 1, wherein the multi-dimensional data set corresponds to data collected from a system, and the method is applied to obtain information for predicting a problem, before the problem develops in the system.
- 22. The method of claim 1, wherein the multi-dimensional data set corresponds to data collected from a system, and the method is applied to obtain information for optimizing the system.
- 23. The method of claim 1, wherein the multi-dimensional data set corresponds to data collected from a system, and the method is applied to obtain information for searching the system.
- 24. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform steps in a method for hierarchical visualization of multi-dimensional data, the method steps comprising:
(a) applying a first dimension-reduction process to a multi-dimensional data set to obtain a first visualization; (b) selecting a subset of the multi-dimensional data set associated with a selected region of the dimension-reduced first visualization; and (c) applying a second dimension-reduction process to the selected subset of the multi-dimensional data set to obtain at least one additional visualization.
- 25. The program storage device of claim 24, wherein (b) and (c) are repeated, until a sufficiently detailed visualization having a desired level of separation of points is obtained.
- 26. The program storage device of claim 24, wherein (b) and (c) are repeated for a further subset associated with a subregion of the selected region.
- 27. A computer system, comprising:
a processor; and a program storage device readable by the computer system, tangibly embodying a program of instructions executable by the processor to perform steps in a method for hierarchical visualization of multi-dimensional data, the method steps comprising:
applying a first dimension-reduction process to a multi-dimensional data set to obtain a first visualization; selecting a subset of the multi-dimensional data set associated with a selected region of the dimension-reduced first visualization; and applying a second dimension-reduction process to the selected subset of the multi-dimensional data set to obtain at least one additional visualization.
- 28. The computer system of claim 27, wherein (b) and (c) are repeated, until a sufficiently detailed visualization having a desired level of separation of points is obtained.
- 29. The computer system of claim 27, wherein (b) and (c) are repeated for a further subset associated with a subregion of the selected region.
- 30. A computer data signal embodied in a transmission medium comprising:
a first segment including dimension-reduction code to perform a dimension-reduction process to a multi-dimensional data set to obtain a first visualization; and a second segment including data selection code to select a subset of the multi-dimensional data set associated with a selected region of the dimension-reduced first visualization wherein the dimension-reduction code is applied at least one time to the selected subset of the multi-dimensional data set to obtain at least one additional visualization.
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of the following co-pending provisional applications:
[0002] (a) Serial No. 60/374,064, filed Apr. 19, 2002 and entitled “PROCESSING MIXED NUMERIC AND/OR NON-NUMERIC DATA”;
[0003] (b) Serial No. 60/374,020, filed Apr. 19, 2002 and entitled “AUTOMATIC NEURAL-NET MODEL GENERATION AND MAINTENANCE”;
[0004] (c) Serial No. 60/374,024, filed Apr. 19, 2002 and entitled “VIEWING MULTI-DIMENSIONAL DATA THROUGH HIERARCHICAL VISUALIZATION”;
[0005] (d) Serial No. 60/374,041, filed Apr. 19, 2002 and entitled “METHOD AND APPARATUS FOR DISCOVERING EVOLUTIONARY CHANGES WITHIN A SYSTEM”;
[0006] (e) Serial No. 60/373,977, filed Apr. 19, 2002 and entitled “AUTOMATIC MODEL MAINTENANCE THROUGH LOCAL NETS”; and
[0007] (f) Serial No. 60/373,780, filed Apr. 19, 2002 and entitled “USING NEURAL NETWORKS FOR DATA MINING”.
Provisional Applications (6)
|
Number |
Date |
Country |
|
60374064 |
Apr 2002 |
US |
|
60374020 |
Apr 2002 |
US |
|
60374024 |
Apr 2002 |
US |
|
60374041 |
Apr 2002 |
US |
|
60373977 |
Apr 2002 |
US |
|
60373780 |
Apr 2002 |
US |