Discovering Regression Rules with Ant Colony Optimization

The majority of Ant Colony Optimization (ACO) algorithms for data mining have dealt with classification or clustering problems. Regression remains an unexplored research area to the best of our knowledge. This paper proposes a new ACO algorithm that generates regression rules for data mining applications. The new algorithm combines components from an existing deterministic (greedy) separate and conquer algorithm—employing the same quality metrics and continuous attribute processing techniques—allowing a comparison of the two. The new algorithm has been shown to decrease the relative root mean square error when compared to the greedy algorithm. Additionally a different approach to handling continuous attributes was investigated showing further improvements were possible

Stone tools and the linguistic capabilities of earlier hominids

The evolution of human manipulative abilities may be clearly linked to the evolution of speech motor control Both creativity and complexity in vocal and manipulative gestures may be closely linked to a single dimension of brain evolution — the evolution of absolute brain size. Inferring the linguistic capabilities of earlier hominids from their lithic artefacts, however, required us to take account of domain-specific constraints on manipulative skill In this article we report on a pilot flint-knapping experiment designed to identify such constraints ‘in action’

Unitary groups over local rings

Structural properties of unitary groups over local, not necessarily commutative, rings are developed, with applications to the computation of the orders of these groups (when finite) and to the degrees of the irreducible constituents of the Weil representation of a unitary group associated to a ramified extension of finite local rings

Characterization of Power-to-Phase Conversion in High-Speed P-I-N Photodiodes

Fluctuations of the optical power incident on a photodiode can be converted into phase fluctuations of the resulting electronic signal due to nonlinear saturation in the semiconductor. This impacts overall timing stability (phase noise) of microwave signals generated from a photodetected optical pulse train. In this paper, we describe and utilize techniques to characterize this conversion of amplitude noise to phase noise for several high-speed (>10 GHz) InGaAs P-I-N photodiodes operated at 900 nm. We focus on the impact of this effect on the photonic generation of low phase noise 10 GHz microwave signals and show that a combination of low laser amplitude noise, appropriate photodiode design, and optimum average photocurrent is required to achieve phase noise at or below -100 dBc/Hz at 1 Hz offset a 10 GHz carrier. In some photodiodes we find specific photocurrents where the power-to-phase conversion factor is observed to go to zero

Using an Ant Colony Optimization Algorithm for Monotonic Regression Rule Discovery

Many data mining algorithms do not make use of existing domain knowledge when constructing their models. This can lead to model rejection as users may not trust models that behave contrary to their expectations. Semantic constraints provide a way to encapsulate this knowledge which can then be used to guide the construction of models. One of the most studied semantic constraints in the literature is monotonicity, however current monotonically-aware algorithms have focused on ordinal classification problems. This paper proposes an extension to an ACO-based regression algorithm in order to extract a list of monotonic regression rules. We compared the proposed algorithm against a greedy regression rule induction algorithm that preserves monotonic constraints and the well-known M5’ Rules. Our experiments using eight publicly available data sets show that the proposed algorithm successfully creates monotonic rules while maintaining predictive accuracy

A Near Infrared Laser Frequency Comb for High Precision Doppler Planet Surveys

We discuss the laser frequency comb as a near infrared astronomical wavelength reference, and describe progress towards a near infrared laser frequency comb at the National Institute of Standards and Technology and at the University of Colorado where we are operating a laser frequency comb suitable for use with a high resolution H band astronomical spectrograph.Comment: 8 pages, 5 figures. Conference Proceedings, New Technologies for Probing the Diversity of Brown Dwarfs and Exoplanets, Shanghai, China, 19-24 July, 2009. Submitted to Eur. Phys. J. Conference

Inducing Probabilistic Grammars by Bayesian Model Merging

We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are {\em incorporated} by adding ad-hoc rules to a working grammar; subsequently, elements of the model (such as states or nonterminals) are {\em merged} to achieve generalization and a more compact representation. The choice of what to merge and when to stop is governed by the Bayesian posterior probability of the grammar given the data, which formalizes a trade-off between a close fit to the data and a default preference for simpler models (`Occam's Razor'). The general scheme is illustrated using three types of probabilistic grammars: Hidden Markov models, class-based $n$-grams, and stochastic context-free grammars.Comment: To appear in Grammatical Inference and Applications, Second International Colloquium on Grammatical Inference; Springer Verlag, 1994. 13 page

Improving music genre classification using automatically induced harmony rules

We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which for each chord the degree and chord category are identified, and covering classical, jazz and pop genre classes. The audio descriptor-based genre classifier contains 206 features, covering spectral, temporal, energy, and pitch characteristics of the audio signal. The fusion of the harmony-based classifier with the extracted feature vectors is tested on three-genre subsets of the GTZAN and ISMIR04 datasets, which contain 300 and 448 recordings, respectively. Machine learning classifiers were tested using 5 × 5-fold cross-validation and feature selection. Results indicate that the proposed harmony-based rules combined with the timbral descriptor-based genre classification system lead to improved genre classification rates

Measurement of carrier envelope offset frequency for a 10 GHz etalon-stabilized semiconductor optical frequency comb

We report Carrier Envelope Offset (CEO) frequency measurements of a 10 GHz harmonically mode-locked, Fabry-Perot etalon-stabilized, semiconductor optical frequency comb source. A modified multi-heterodyne mixing technique with a reference frequency comb was utilized for the measurement. Also, preliminary results from an attempt at f-2f self-referencing measurement are presented. The CEO frequency was found to be similar to 1.47 GHz for the particular etalon that was used