We use a standard tree-structure representation for each individual. The GP constructs new attributes out of the continuous (real-valued) attributes of the data set being mined. Each individual corresponds to a candidate new attribute. The terminal set consists of all the continuous attributes in the data being mined. The function set consists of four arithmetic operators (+, -, *, /) and two r...

A set of experiments is described which use Genetic Algorithms (GAs) to find the synthesizer parameters required to synthesize a target sound. Comparisons between the target and candidate sounds (for the algorithms’ fitness functions) are calculated via a mapping from the sound data to a set of timbral, perceptual, and statistical sound attributes, many of which have been used in recent machine...

For data mining, reducing the unnecessary redundant attributes which was known as attribute reduction (AR), in particular, reducts with minimal cardinality, is an important preprocessing step. In the paper, by a coding method of combination subset of attributes set, a novel search strategy for minimal attribute reduction based on rough set theory (RST) and fish swarm algorithm (FSA) is proposed...

Our basic idea is to employ association rule for the purpose of data quality measurement. Strong rule generation is an important area of data mining. We purpose a Genetic Algorithm to generate high quality Association Rules with four metrics they are confidence, completeness, interestingness and comprehensibility. These metrics are combined as an objective fitness function. Fitness function eva...

Real world datasets may be continuous. Many data analysis algorithms work efficiently on discrete data while some other algorithms work only on discrete data. Thus the continuous datasets are discretized as a pre-process step to knowledge acquisition. Attribute discretization is the process of reducing the domain of a continuous attribute with irreducible and optimal set of cuts, while preservi...

Significance and relevance of certain features are obtained by various techniques. Feature subset selection involves summarizing mutual associations between class decisions and attribute values in a pre-classified database. In this paper genetic algorithm is used to find the relevant set of features by optimizing the fitness function and using the operators like crossover and mutation. Fuzzy lo...

Size is a fundamental attribute impacting cellular design, fitness, and function. Size homeostasis requires a doubling of cell mass with each division. In yeast, division is delayed until a critical size has been achieved. In metazoans, cell cycles can be actively coupled to growth, but in certain cell types extracellular signals may independently induce growth and division. Despite a long hist...

The paper presents a method which shows a significant improvement in discovering the path over the distance vector protocol. The proposed method is a multi-parameter QoS along with the fitness function which shows that it overcomes the limitation of DV like routing loops by spanning tree approach, count-to-infinity problem by decision attribute. The input considered is a topology satisfying the...

Social networks are typical attributed networks with node attributes. Different from traditional attribute community detection problem aiming at obtaining the whole set of communities in the network, we study an application-oriented problem of mining an application-aware community organization with respect to specific concerned attributes. The concerned attributes are designated based on the re...