We present an algorithm for inductive learning from examples that outputs an ordered list of if-then rules as its hypothesis. The algorithm uses a combination of greedy and branch-and-bound techniques, and naturally handles noisy or stochastic learning situations. We also present the results of an empirical study comparing our algorithm with Quinlan's C4.5 on 1050 synthetic data sets. We nd tha...

The original dataset consists of data on over four million connections each described by 42 attributes (e.g., duration, protocol, etc.) and identified either as normal traffic or one of 24 attack types. Our simulation is designed as follows: 1. A total of 20,000 connections were randomly selected from the original dataset to form the simulation training set; 16 attack types were represented in ...

The development of a software system which can detect and identify the ight calls of migrating birds is reported. The system rst produces a spectrogram using a Discrete Fourier transform. Calls are detected in the spectrogram using an ad-hoc combination of local peak-nding and a connectedness measure. Attributes are extracted both globally from the call and from a window moved incrementally thr...

In our days, interest to the class of inductors on the basis of decision trees does not weaken, especially in the context of Data Mining paradigm . At the same time most widespread Quinlan algorithms ID3 and C4.5, as we show in the paper, are not the best. It is therefore possible to see the successful attempts of creation another heuristic splitting criteria for the algorithms of synthesis of ...

Physarum displays two vegetative cell types, uninucleate myxamoebae and multinucleate plasmodia. Mutant myxamoebae of Physarum resistant to the antitubulin drug methylbenzimidazole-2-yl-carbamate (MBC) were isolated. All mutants tested were cross-resistant to other benzimidazoles but not to cycloheximide or emetine. Genetic analysis showed that mutation to MBC resistance can occur at any one of...

Introduction Named-entity recognition (NERC) is the identification of proper names in text and their classification as different types of named entity. A typical NERC system consists of a lexicon and a grammar. The lexicon is a set of gazetteer lists, containing names that are known beforehand and have been classified into named-entity types, such as persons, organisations, locations etc. The g...

To date research in intelligent mobile agent have mainly focused on the development of a large and smart “brain” to enable robot autonomy (Arkin 2000; Murphy 2000). They are, however, facing a bottleneck of complexity due to the dynamics of the unstructured environments. Steering away from this smart brain approach, this chapter investigates the use of low level intelligence, such as insect eye...

We describe an experimental study of pruning methods for decision tree classi ers in two learning situations: minimizing loss and probability estimation. In addition to the two most common methods for error minimization, CART's cost-complexity pruning and C4.5's errorbased pruning, we study the extension of cost-complexity pruning to loss and two pruning variants based on Laplace corrections. W...

The development of a software system which can detect and identify the ight calls of migrating birds is reported. The system rst produces a spectrogram using a Discrete Fourier transform. Calls are detected in the spectrogram using an ad-hoc combination of local peak-nding and a connectedness measure. Attributes are extracted both globally from the call and from a window moved incrementally thr...