Download Algorithms for Clustering Data by Anil K. Jain PDF

By Anil K. Jain

Show description

Read Online or Download Algorithms for Clustering Data PDF

Similar algorithms books

Automated Planning: Theory & Practice (The Morgan Kaufmann Series in Artificial Intelligence)

Computerized making plans know-how now performs an important position in numerous hard functions, starting from controlling house autos and robots to enjoying the sport of bridge. those real-world purposes create new possibilities for synergy among idea and perform: gazing what works good in perform results in larger theories of making plans, and higher theories bring about higher functionality of sensible purposes.

Web Data Management

The net and world-wide-web have revolutionized entry to info. clients now shop details throughout a number of structures from own desktops, to smartphones, to web content reminiscent of Youtube and Picasa. for this reason, information administration recommendations, equipment, and strategies are more and more considering distribution issues.

Algorithms and Data Structures for External Memory (Foundations and Trends(R) in Theoretical Computer Science)

Information units in huge functions are usually too great to slot thoroughly contained in the computer's inner reminiscence. The ensuing input/output verbal exchange (or I/O) among quick inner reminiscence and slower exterior reminiscence (such as disks) could be a significant functionality bottleneck. Algorithms and knowledge constructions for exterior reminiscence surveys the cutting-edge within the layout and research of exterior reminiscence (or EM) algorithms and information constructions, the place the aim is to use locality and parallelism on the way to decrease the I/O bills.

Genetic Algorithms and Genetic Programming in Computational Finance

After a decade of improvement, genetic algorithms and genetic programming became a commonly permitted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering quantity committed completely to a scientific and entire evaluate of this topic.

Additional info for Algorithms for Clustering Data

Example text

Cards described in 2-5 form card type 17. For more details of this procedure see card types 5, 16 and 17 and the description of NKN~WN on the problem definition card (type 2). Third, for each regression equation calculated, the maximum likelihood F-ratio is computed. sion equation. The user can specify confidence limits on the F-ratio for each regresIf the F-ratio for a given N falls below its corresponding confidence 28 limit, the program will stop. type 6 and IST~PF To use this procedure see the descriptions of card on the problem definition card.

This card type are 5 and 10. The values for The program will expect card types 16 and 17 which were punched in an earlier job for N ~ 5 and N = 10. eJPF = O. These values provide the confidence limits for the F-ratio of each regression equation. If an equation's F-ratio is less than the confidence limit, the program will print that the result is not significant. = 2, the program will try to go IST,eJPF = 1, it will resume the same If IST,eJPF on to the next problem (next title card). If problem with the next equation.

The optimal regression program always works with a set of N - 1 independent variables and then chooses variable N by trying all possible solutions. the maximum number of variables that can be forced in is N - 1. Therefore, If N0IN, the number of vari ab les actually in the regress ion equati on, is greater than or equal to N, and if no variables can be pivoted out, the program will print the values of Nand N0IN and then stop. This means that N variables cannot be forced into an equation. 36 Values are read into array KLEVEL.

Download PDF sample

Rated 4.85 of 5 – based on 20 votes