Adaptive fuzzy partition in database mining: application to olfaction
نویسندگان
چکیده
منابع مشابه
Adaptive fuzzy partition in database mining: application to olfaction
A data set of 412 olfactory compounds, divided into animal, camphoraceous, ethereal and fatty olfaction classes, was submitted to an analysis by a Fuzzy Logic procedure called Adaptive Fuzzy Partition (AFP). This method aims to establish molecular descriptor/chemical activity relationships by dynamically dividing the descriptor space into a set of fuzzily partitioned subspaces. The ability of t...
متن کاملMining fuzzy association rules in a bank-account database
This paper describes how we applied a fuzzy technique to a data-mining task involving a large database that was provided by an international bank with offices in Hong Kong. The database contains the demographic data of over 320,000 customers and their banking transactions, which were collected over a six-month period. By mining the database, the bank would like to be able to discover interestin...
متن کاملA Model for Mining Multilevel Fuzzy Association Rule in Database
The problem of developing models and algorithms for multilevel association mining pose for new challenges for mathematics and computer science. These problems become more challenging, when some form of uncertainty like fuzziness is present in data or relationships in data. This paper proposes a multilevel fuzzy association rule mining models for extracting knowledge implicit in transactions dat...
متن کاملFuzzy hypergraph and fuzzy partition
In this paper, the concept of hypergraph is extended to the fuzzy hypergraph. In the fuzzy hypergraph, the concepts of a-cut hypergraph, strength of edge and dual fuzzy hypergraph are developed. It is shown that the fuzzy hypergraph and a-cut hypergraph are useful to represent a fuzzy partition. An application example also shows that the strength of edge can be used to decompose the data set in...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Data Science Journal
سال: 2002
ISSN: 1683-1470
DOI: 10.2481/dsj.1.99