Common induction systems that construct decision-trees have been reported to operate unsatisfactorily when there are attributes with varying numbers of discrete possible values. This paper highlights the deficiency in the evaluation of the relevance of attributes and examines a proposed solution. An alternative method of selecting an attribute is introduced which permits the use of redundant at...

owing to the oncoming needs and increasing the population of lake urmia watershed, providing equilibrium  between water supply and demand seems quite challenging and the lake cannot be successful in meeting its ecological demands in this critical condition. in this unfavorable situation, water resources must be managed through a sustainable context. with this knowledge in hand, a multi attribut...

The attributes contributing to the differences perceived between microphones (when auditioning recordings made with those microphones) are not clear from previous research. Consideration of technical specifications and expert opinions indicated that recording five programme items with eight studio and two microelectromechanical system microphones could allow determination of the attributes rela...

Multi-attribute auctions allow agents to sell and purchase goods and services taking into account more attributes besides the price (e.g. service time, tolerances, qualities, etc.). In this paper we analyze attributes involved during the auction process and propose to classify them between verifiable attributes, unverifiable attributes and auctioneer provided attributes. According to this class...

Data mining is a collection of analytical techniques to uncover new trends and patterns in massive databases. These data mining techniques stress visualization to thoroughly study the structure of data and to check the validity of the statistical model fit which leads to proactive decision making. Discriminant analysis is one of the data mining tools used to discriminate a single classification...

Discriminant analysis is one of the classical classification techniques used to discriminate a single categorical variable using multiple attributes. Discriminant analysis also assigns observations to one of the pre-defined groups based on the knowledge of the multi-attributes. When the distribution within each group is multivariate normal, a parametric method can be used to develop a discrimin...

We analyse the biases of eleven mtasures for estimating the quality of the mult ivalued attributes The values of information gain Jmeasure, gini-index and relevance tend to lin early increase with the number of values of an attr ibute The values of gam-ratio dis tance measure, Relief and the weight of evidence decrease for informative attributes and increase for irrelevant attributes The bias o...

The authors propose a Multi Attributes approach to meet the demand of personalized tourist tours into cultural cities. Respecting to others works present into the literature, in this paper the decisional process includes two phases and a high number of variables that don’t increase the complexity of the problem. A real application in an Italian city, Florence, is presented to demonstrate the gr...

End-users frequently prefer to use spreadsheets as a medium for storing simple data. There are a number of commonly used data arrangements to cope with data items that are connected with a many-many relationship. These arrangements offer the end-user simplicity in data entry and simple reporting. However as the application evolves it soon becomes apparent that these arrangements of data have se...