Load CSV data from file. Load CSV data from textfield. Averaged height0 repr. elements barchart. Averaged height extended repr. elements barchart. Objects averaged height extended. Aim of the programm. LPOM stands for Local Partial Order Model. LPOM0 and LPOMext are approximations to calculate the average height, hav, of partially ordered sets posets. More documentation can be found at. To run this module for a better insight. Select a dataset, there you also can load your own data set.

OVERVIEW

The domain lpom.pyhasse.org currently has a traffic ranking of zero (the lower the more traffic). We have parsed twenty pages within the site lpom.pyhasse.org and found one hundred and three websites referencing lpom.pyhasse.org.
Pages Parsed
20
Links to this site
103

LPOM.PYHASSE.ORG TRAFFIC

The domain lpom.pyhasse.org has seen varying levels of traffic until the end of the year.
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LINKS TO WEBSITE

acm.pyhasse.org

Load CSV data from textfield. Find attribute pairs causing incomparabilities. Full documentation about the moduel is available at. To run this module for a better insight. Select a dataset, there you also can load your own data set. Export your results, e.

chain.pyhasse.org

Load CSV data from textfield. The module Chain allows a detailled analysis of the chains, when start-, endpoints and a minimum number of the so-called height are selected. For example the similarity among chains can be evaluated by the Tanimoto-similarity coefficient. To run this module for a better insight.

copeland.pyhasse.org

Load CSV data from textfield. A copeland matrix will be derived. Each entry of the Copeland matrix has - - values according to x y or x y. Then the rowsum of copeland matrix gives a ranking. To run this module for a better insight. Select a dataset, there you also can load your own data set.

fuzzy.pyhasse.org

Load CSV data from textfield. Application of fuzzy concepts within the framework of partial orders is one interesting option to take into regard that not any slight numerical difference is considered as relevant for a ranking. Full documentation about the moduel is available at. To run this module for a better insight.

spyout.pyhasse.org

Load CSV data from textfield. First inspection of data-driven partially ordered sets. To run this module for a better insight. Select a dataset, there you also can load your own data set. Export your results, e.

WHAT DOES LPOM.PYHASSE.ORG LOOK LIKE?

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LPOM.PYHASSE.ORG SERVER

We detected that the main page on lpom.pyhasse.org took seven thousand nine hundred and thirty-eight milliseconds to come up. Our web crawlers could not discover a SSL certificate, so our crawlers consider this site not secure.
Load time
7.938 sec
SSL
NOT SECURE
IP
5.9.165.108

SERVER SOFTWARE

We observed that this website is implementing the nginx/1.10.1 server.

SITE TITLE

lpom.pyhasse.org

DESCRIPTION

Load CSV data from file. Load CSV data from textfield. Averaged height0 repr. elements barchart. Averaged height extended repr. elements barchart. Objects averaged height extended. Aim of the programm. LPOM stands for Local Partial Order Model. LPOM0 and LPOMext are approximations to calculate the average height, hav, of partially ordered sets posets. More documentation can be found at. To run this module for a better insight. Select a dataset, there you also can load your own data set.

PARSED CONTENT

The domain lpom.pyhasse.org had the following on the web page, "Load CSV data from textfield." I observed that the website said " LPOM stands for Local Partial Order Model." They also stated " LPOM0 and LPOMext are approximations to calculate the average height, hav, of partially ordered sets posets. More documentation can be found at. To run this module for a better insight. Select a dataset, there you also can load your own data set."

SEE OTHER WEBSITES

match Home Page

MATCH Communications in Mathematical and in Computer Chemistry. 2 volumes per year, each with 3 issues.

spyout.pyhasse.org

Load CSV data from textfield. First inspection of data-driven partially ordered sets. To run this module for a better insight. Select a dataset, there you also can load your own data set. Export your results, e.

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