Many of the supervised learning algorithms only work with spaces of discrete attributes. Some of the methods proposed in the bibliography focus on the discretization towards the generation of decision rules. This work provides a new discretization algorithm called USD (Unparametrized Supervised Discretization), which transforms the infinite space of the values of the continuous attributes in a ...

In this article, some simple methods for testing and estimating the parameters of some discrete distributions are proposed. For hypothesis testing, a new test is obtained by combining the usual exact test and an alternative exact test. The exact properties of the usual exact test, the alternative exact test and the combined test are evaluated numerically for the binomial and Poisson distributio...

Interval temporal logics provide a natural framework for temporal reasoning about interval structures over linearly ordered domains, where intervals are taken as the primitive ontological entities. The most influential propositional interval-based logic is probably Halpern’s and Shoham Modal Logic of Time Intervals, a.k.a. HS. While most studies focused on the computational properties of the sy...

As cognitive models are developed that are meant to apply to a broad range of phenomena, it is necessary to evaluate how successfully they do so. This is commonly done by measures such as the Mean Squared Error. We propose and demonstrate an alternate approach based on a measure of statistical equivalence. Instead of using sample means, this method uses confidence intervals, and places an upper...

We show that a particular noncommutative geometry, sometimes called angular or $\rho$-Minkowski, requires the spectrum of time be discrete. In this space variable is not commuting with in cylindrical coordinates. The possible values can take go from minus infinity to plus infinity, equally spaced by scale noncommmutativity. Possible self-adjoint extensions "time operator" are discussed. They gi...

This paper surveys some signi ̄cant applications of interval analysis to robust control ̄eld. Interval analysis is specially powerful in bounding the ranges of functions while providing mathematically rigorous results. This capability is especially welcome in robust control, since a variety of analysis and design problems can be cast in the evaluation of the range of functions over intervals. To...

A methodology for modeling temporal (timesensitive) aspects of discrete-event systems is presented. A formalism of temporal logic which incorporates both point and interval descriptions of time is formulated, which is an extension of Allen’s interval logic [1]. A formal axiomatic system of this point-interval logic is presented. A graph model is shown to implement the axiomatic system of point-...

A graph is a probe interval graph if its vertices correspond to some set of intervals of the real line and can be partitioned into sets P and N so that vertices are adjacent if and only if their corresponding intervals intersect and at least one belongs to P . We characterize the 2-trees which are probe interval graphs and extend a list of forbidden induced subgraphs for such graphs created by ...

We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we use linearized equations to examine the evolution near that neighborhood. The underlying idea is that points of stable periodic orbit are associated with in...

In many consumer-resource systems the consumer population has synchronized reproduction at regular intervals (e.g., years) but consumes the resource and dies continuously, while the resource population grows continuously or has overlapping generations that are short relative to the time between consumer reproductive events. Such systems require "semi-discrete" models that have both discrete and...