Method, system, and computer program for visually approximating

Computer graphics processing and selective visual display system – Computer graphics processing – Graph generating

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

G06F 1500

Patent

active

058618910

ABSTRACT:
A method, system, and computer program product are provided for visually approximating a scatter plot. Bins of scattered data points are formed. Each axis of a scatter plot is discretized according to a binning resolution. Bin positions along each discretized scatter plot axis are determined from the bin numbers. The bins, which represent a cloud of scattered data points, are volume rendered as splats. The opacity of each splat is a function of the number (count) of data points in a corresponding bin. In one example, the opacity of a splat is determined by the following equation:

REFERENCES:
patent: 3816726 (1974-06-01), Sutherland et al.
patent: 4868771 (1989-09-01), Quick et al.
patent: 4928247 (1990-05-01), Doyle et al.
patent: 4994247 (1991-02-01), Usami et al.
patent: 5043920 (1991-08-01), Malm et al.
patent: 5072395 (1991-12-01), Bliss et al.
patent: 5150457 (1992-09-01), Behm et al.
patent: 5164904 (1992-11-01), Sumner
patent: 5282262 (1994-01-01), Kurashige
patent: 5295243 (1994-03-01), Robertson et al.
patent: 5307456 (1994-04-01), MacKay
patent: 5459829 (1995-10-01), Doi et al.
patent: 5528735 (1996-06-01), Strasnick et al.
patent: 5555354 (1996-09-01), Strasnick et al.
patent: 5732230 (1998-03-01), Cullen et al.
Aha, D.W. et al., "Instance-Based Learning Algorithms," Machine Learning, vol. 6, No. 1, pp. 37-66 (Jan. 1991).
Almuallim, H. and Dietterich, T.G.,"Learning Boolean Concepts in the Presence of Many Irrelevant Features, " Artificial Intelligence, vol. 69, No. 1-2, pp. 279-305 (Sep. 1994).
"Angoss Software Announces Knowledge Studio Data Mining Solution," http://www.pathfinder.com/@@xIEkOgYAVjbJZjKM/money/latest/press/PW/19970ct 27/92. Angoss Software Corporation, pp. 1-2, Oct. 1997.
"Angoss Software's KnowledgeSeeker(TM) Compatible with SAS Institute," http://www.newswire.ca/releases/September1997/18/c3915.html, pp. 1-2, Canada Newswire, Sep. 1997.
Breiman et al., Classification and Regression Trees, Wadsworth International Group, entire book (1984).
Cestnik, B., "Estimating Probabilities: A Crucial Task in Machine Learning," Proceedings of the 9th European Conference on Artificial Intelligence, pp. 147-149 (Aug. 1990).
"Companies in Data Mining and Knowledge Discovery," http://kdnuggets.com/companies.html, pp. 1-4, Last updated: Oct. 31, 1997.
Cormen, T.H., et al., Introduction to Algorithms, The MIT Press, pp. 263-280 (1990).
Cover and Thomas, Elements of Information Theory, Wiley Interscience, entire book, 1991.
Dasarathy, B.V., "Nearest Neighbor (NN) Norms: (NN) Patterns Classificaion Techniques," (IBL), IEEE Computer Society Press, pp. 1-30 (1990).
"Data Mining and Knowledge Discovery References," http://kdnuggets.com/references.html, pp. 1-3, Last updated: Oct. 29, 1997.
Domingos, P. and Pazzani, M., "Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier," Machine Learning: Proceedings of the 13th International Conference (ICML '96), pp. 105-112 (1996).
Duda, R. and Hart, P., Pattern Classification and Scene Analysis, Wiley, entire book, (1973).
Fairchild, K.M., "Information Management Using Virtual Reality-Based Visualizations," Virtual Reality Applications and Explorations, ed. A. Wexelblat, Academic Press, Inc., pp. 45-74, Copyright (1993), Publication date Jul. 1, 1993.
Fisher, R.A., "The use of multiple measurements in taxonomic problems," Annals of Eugenics, vol. 7., No. 1, pp. 179-188 (1936).
Friedman, J. H. et al., "Lazy Decision Trees," Proceedings of the Thirteenth National Conference on Artificial Intelligence, AAAI Press and the MIT Press, vol. 1, pp. 717-724 (1996).
Good, I.J., The Estimation of Probabilities: An Essay on Modern Bayesian Methods, pp. xi-xii, MIT Press, pp. 1-79, (1965).
"IBM Digs Deep for Data Mining `Gold`, " http://www.software.ibm.com/data/intellimine/factsheet.html, pp. 1-8, IBM Corporation, Copyright 1997.
"KD Mine: Data Mining and Knowledge Discovery," http://kdnuggets.com/index.sub.-- kdm.html. p. 1, Knowledge Discovery Nuggets, Copyright 1997, Last updated: Oct. 31, 1997.
Kittler, J., "Feature Selection and Extraction," Handbook of Pattern Recognition and Image Processing. Chapter 3, pp. 59-83, Academic Press, Inc., 1986.
Knuth, A., The Art of Computer Programming, Addison-Wesley, vol. 2, pp. 506-550 (1973).
Kohavi, R., "Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid," In Data Mining and Visulaization, Silicon Graphics, Inc., from The Second International Conference on Knowledge Discovery and Data Mining (1996).
Kohavi, R., "A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection," Proceedings of the 14th International Joint Conference on Artifical Intelligence, Stanford University, 1995.
Kohavi, R. and John, G., "Wrappers for Feature Subset Selection," http://robotics.stanford.edu/-{ronnyk,gjohn}, May 20, 1997.
Kohavi, R. And Li, C., "Oblivious Decision Trees, Graphs, and Top-Down Pruning," Proceedings of the 14th International Joint Conference on Artificial Intelligence, Chriss S. Mellish (Ed.), Morgan Kaufmann Pulishers, Inc., pp. 1071-1077 (1995).
Kohavi, R. and Sommerfield, D., "Feature Subset Selection Using the Wrapper Model: Overfitting and Dynamic Search Space Topology," Proceedings of the First International Conference on Knowledge Discovery and Data Mining, pp. 192-197 (Aug. 1995).
Kohavi, R. et al., "Data Mining using MLC++: A Machine Learning Library in C++," Tools With AI, pp. 234-245 (1996).
Kononenko, I., "Inductive and Bayesian Learning in Medical Diagnosis," Applied Artificial Intelligence, vol. 7, pp. 317-337 (1993).
Langley, P. and Sage, S., "Induction of Selective Bayesian Classifiers," Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann Publishers, Inc., pp. 399-406 (Jul. 1994).
Langley, P. and Sage, S., "Oblivious Decision Trees and Abstract Cases," Working Notes of the AAAI-94 Workshop on Case-Based Reasoning, AAAI Press, pp. 113-117 (1994).
Langley, P., et al., "An Analysis of Bayesian Classifiers," Proceedings of the Tenth National Conference on Artificial Intellilgence, pp. 223-228 (Jul. 1992).
Lincoff, G., National Audubon Society Field Guide to North American Mushrooms, New York, pp. 9-32, (1981).
Mangasarian, O. L. and Wolberg, W. H., "Cancer Diagnosis Via Linear Programming," SIAM News, vol. 23, No. 5, pp. 1&18 (Sep. 1990).
Michie, et al., Machine Learning, Neural and Statistical Classification, Ellis Norwood United, entire book, (1994).
Murthy, S. et al., "Randomized induction of oblique decision trees," Proceedings of the Eleventh National Conference on Artificial Intelligence, AAI Press/MIT Press, pp. 322-327 (1993.
"Other Web Sites for Data Mining and Knowledge Discovery," http://kdnuggets.com/websites.html, pp. 1-3, Last updated: Sep. 10, 1997.
Quinlan, J.R., C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, Inc., pp. 17-26 (1993).
Quinlan, J.R., "Induction of Decision Trees," Machine Learning, vol. 1, No. 1, pp. 81-106 (1986).
Rendell, L. and Seshu, R., "Learning hard concepts through constructive induction: framework and rationale," Computational Intelligence, vol. 6, No. 4, pp. 247-270 (Nov. 1990).
"SAS Data Mining Solution," http://www.sas.com/software/data.sub.-- mining/whitepapers/solution.html, pp. 1-6, SAS Institute Inc., Copyright 1997, Last Updated Sep. 26, 1997.
Schaffer, C., "A Conservation Law for Generalization Performance," Machine Learning: Proceedings of the Eleventh International Conference, Morgan Kaufmann Publishers, Inc., pp. 259-265 (1994.
Shavlik, J.W. and Dietterich, T.G. (Eds.), Readings in Machine Learning, Morgan Kaufmann Publishers, Inc., entire book, (1990).
"S*i*ftware: Tools for Data Mining and Knowledge Discovery," http://kdnuggets.com/siftware.html., pp. 1-2, Last updated: Oct. 31, 1997.
Thrun et al., "The Monk's Problems: A Performance Comparison of Different Learning Algorithms," Technical Report CMU-CS-91-197, Carnegie Mellon University pp. i-x and 1-112, (1991).
Utgoff, P., "Perceptron Trees: A Case Study in Hybrid Concept Representation," Proceedings of the Seventh National Conference on Artificial

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Method, system, and computer program for visually approximating does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Method, system, and computer program for visually approximating , we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method, system, and computer program for visually approximating will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1250541

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.