Analysis of monotonicity properties of some rule interestingness measures

One of the crucial problems in the field of knowledge discovery is development of good interestingness measures for evaluation of the discovered patterns. In this paper, we consider quantitative, objective interestingness measures for "if..., then... " association rules. We focus on three popular interestingness measures, namely rule interest function of Piatetsky-Shapiro, gain measure of Fukuda et al., and dependency factor used by Pawlak. We verify whether they satisfy the valuable property M of monotonic dependency on the number of objects satisfying or not the premise or the conclusion of a rule, and property of hypothesis symmetry (HS). Moreover, analytically and through experiments we show an interesting relationship between those measures and two other commonly used measures of rule support and anti-support

Micrurus ruatanus

Number of Pages: 2Integrative BiologyGeological Science

FLIP - Multiobjective Fuzzy Linear Programming Package

FLIP (Fuzzy LInear Programming) is a package designed to help in analysis of multiobjective linear programming (MOLP) problems in an uncertain environment. The uncertainty of data is modeled by L-R type fuzzy numbers. They can appear in the objective functions as well as on the both sides of the constraints. The input data to the FLIP package include the characteristics of the analyzed fuzzy MOLP problem, i.e., the number of criteria, constraints and decision variables, fuzzy cost coefficients for every objective and fuzzy coefficients of LHS and RHS for all constraints. The data loading is supported by a graphical presentation of fuzzy coefficients. The calculation is preceded by a transformation of the fuzzy MOLP problem into a multiobjective linear fractional program. It is then solved with an interactive method using a linear programming procedure as the only optimiser. In every iteration, one gets a series of solutions that are presented very clearly in a graphical and numerical form. In FLIP, interaction with the user takes place at two levels: first, when safety parameters have to be defined in the transformation phase, and second, when the associate deterministic problem is solved. The package is written in TURBO-Pascal and can be used on microcomputers compatible with IBM-PC XT/AT with hard disc and a graphic card

The LBS package - a microcomputer implementation of the Light Beam Search method for the multiple -objective non-linear mathematical programming

The paper presents the LBS package which is a microcomputer implementation of the Light Beam Search method. The software has been designed to support interactive analysis of multiple-objective continuous non-linear mathematical programming problems. At the decision phase of the interactive procedure, a sample of points, composed of the current point and a number of alternative proposals, is presented to the decision maker (DM). The sample is constructed to ensure a relatively easy evaluation of the sample by the DM. To this end an outranking relation is used as a local preference model in a neighborhood of the current point. The outranking relation is used to define a sub-region of the non-dominated set where the sample presented to the DM comes from. The DM has two possibilities to move from one sub-region to another which better fits his/her preferences. The first possibility consists in specifying a new reference point which is then projected onto the non-dominated set in order to find a better non-dominated point. The second possibility consists in shifting the current point to a selected point from the sub-region. In both cases, a new sub-region is defined around the updated current point. This technique can be compared to projecting a focused beam of light from a spotlight at the reference point onto the non-dominated set; the highlighted sub-region changes when either the reference point or the point of interest in the non-dominated set are changed. The LBS package has been implemented in Turbo Pascal within the MS-Windows environment. The package includes two versions of the LBS executable program and a set of example problems. The LBS program is composed of three modules: the problem definition module, the solver module and the interactive analysis module. The problem definition module allows for defining multiple-objective non-linear problems in a natural text form. It supports also checking the correctness of the problem definition and compilation of a problem defined in a text form to an internal format. The solver module is exchangeable and any non-linear optimizer fining to the specified interface can be used in this module. The two versions of the LBS program differ just by the solver used. The first one, coming from the PINOKIO package, is an implementation of the Generalized Reduced Gradient method (GRG). The second one, coming from the DIDAS-N package is an implementation of the Penalty Shifting Method. The interactive analysis module makes an extensive use of computer graphics to help in the perception of a large amount of information. The graphical windows environment allows for simultaneous presentation of different kinds of information and mixing of textual, numerical and graphical forms of presentation

Survey of finance companies, 1996

Finance companies are major suppliers of credit to consumers and businesses. The sector is made up of roughly 1,250 nondepository financial institutions, with 20 firms accounting for three-fourths of the receivables. The Federal Reserve System has been surveying the assets and liabilities of finance companies, typically at five-year intervals, since June 1955. This article summarizes the results of the 1996 survey. Special features of that survey are a breakdown of automobile leases into consumer and business components and, relative to previous surveys, greater detail on the composition of real estate credit and more information on securitized loans and leases.Finance companies

MPS - Decision Support System for Multiobjective Project Scheduling

The report presents a decision support system (DSS) for multiobjective project scheduling under multiple-category resource constraints. It handles quite a general class of nonpreemptive scheduling problems with renewable, nonrenewable and doubly-constrained resources, multiple performing modes of activities, precedence constraints in the form of an activity network and multiple project performance criteria of time and cost type. The DSS has been implemented on a microcomputer compatible with IBM PC, and called MPS. It is based on three kinds of heuristics: parallel priority rules, simulated annealing and branch-and-bound. The last algorithm can even yield exact solutions when sufficient processing time is available. Some parts of the MPS are interactive, in particular, the search for a best compromise schedule. Graphical facilities enable a thorough evaluation of feasible schedules. The report starts with a methodological guide presenting the problem formulation and the three heuristics. Then, the general scheme of the MPS is given together with an executive guide. An expanding menu and all its options are described and illustrated with a simple example. The last part presents a real problem solving consisting in scheduling 40 farm activities

An improved direct colorimetric method for the quantitative analysis of urinary hippuric acid as an index of toluene exposure

An improved direct colorimetric method for determining the concentration of urinary hippuric acid as an index of toluene exposure was described. One tenth ml of urine was diluted with 0.4 ml 0.01 M phosphate buffer H 6.9 and mixed with 0.5 ml pyridine. The mixture was layered on 0.2 ml benzenesulfonyl chloride. The reaction was started by mixing for one min with a mechanical shaker. The colored solution was allowed to stand for 30 min, diluted with 5 ml ethanol, and absorbance measured at 410 nm within 30 min after the dilution. The coefficient of variation of this method was 6% and the recovery 103% when urine contains about 0.2-0.5 mg hippuric acid per ml of urine. The concentration was linear up to 2.0 mg per ml hippuric acid in a specimen.</p

Identification of Biodiversity and Other Forest Attributes for Sustainable Forest Management: Siberian Forest Case Study

This paper attempts to identify characteristics of biodiversity and other (forest) ecosystem conditions that are considered essential for a description of ecosystem functioning and development of sustainable forest management practices in the Siberian forests. This is accomplished through an analysis of net primary production of phytomass (NPP) which acts as a proxy for ecosystem functioning. Rough Sets (RS) analysis is applied to study the Siberian ecoregions classified into compact and cohesive NPP performance classes. Through a heuristic procedure, a reduced set of attributes is generated for a NPP classification problem. In order to interpret relationships between various forest characteristics, so-called "interesting rules" are generated on a basis of reduced problem description. These "interesting rules" provide means to draw conclusions in the form of knowledge statements about functioning of the Siberian forests