Efficient Discovery of Expressive Multi-label Rules using Relaxed Pruning

Being able to model correlations between labels is considered crucial in multi-label classification. Rule-based models enable to expose such dependencies, e.g., implications, subsumptions, or exclusions, in an interpretable and human-comprehensible manner. Albeit the number of possible label combinations increases exponentially with the number of available labels, it has been shown that rules with multiple labels in their heads, which are a natural form to model local label dependencies, can be induced efficiently by exploiting certain properties of rule evaluation measures and pruning the label search space accordingly. However, experiments have revealed that multi-label heads are unlikely to be learned by existing methods due to their restrictiveness. To overcome this limitation, we propose a plug-in approach that relaxes the search space pruning used by existing methods in order to introduce a bias towards larger multi-label heads resulting in more expressive rules. We further demonstrate the effectiveness of our approach empirically and show that it does not come with drawbacks in terms of training time or predictive performance.Comment: Preprint version. To appear in Proceedings of the 22nd International Conference on Discovery Science, 201

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

Exploiting dependencies between labels is considered to be crucial for multi-label classification. Rules are able to expose label dependencies such as implications, subsumptions or exclusions in a human-comprehensible and interpretable manner. However, the induction of rules with multiple labels in the head is particularly challenging, as the number of label combinations which must be taken into account for each rule grows exponentially with the number of available labels. To overcome this limitation, algorithms for exhaustive rule mining typically use properties such as anti-monotonicity or decomposability in order to prune the search space. In the present paper, we examine whether commonly used multi-label evaluation metrics satisfy these properties and therefore are suited to prune the search space for multi-label heads.Comment: Preprint version. To appear in: Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2018. See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3074 for further information. arXiv admin note: text overlap with arXiv:1812.0005

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

The objective of this study was to estimate genetic and phenotypic correlations of body weight at 6 weeks of age (BW6), as well as final carcass yield, and moisture, protein, fat and ash contents, using data from 3,422 F2 chickens originated from reciprocal cross between a broiler and a layer line. Variance components were estimated by the REML method, using animal models for evaluating random additive genetic and fixed contemporary group (sex, hatch and genetic group) effects. The heritability estimates (h2) for BW6, carcass yield and percentage of carcass moisture were 0.31 ± 0.07, 0.20 ± 0.05 and 0.33 ± 0.07, respectively. The h2 for the percentages of protein, fat and ash on a dry matter basis were 0.48 ± 0.09, 0.55 ± 0.10 and 0.36 ± 0.08, respectively. BW6 had a positive genetic correlation with fat percentage in the carcass, but a negative one with protein and ash contents. Carcass yield, thus, appears to have only low genetic association with carcass composition traits. The genetic correlations observed between traits, measured on a dry matter basis, indicated that selection for carcass protein content may favor higher ash content and a lower percentage of carcass fat

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic power spectrum between redshifts 0.6 and 1.0

We analyse the clustering of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 luminous red galaxy sample (DR16 eBOSS LRG) in combination with the high redshift tail of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey Data Release 12 (DR12 BOSS CMASS).We measure the redshift space distortions (RSD) and also extract the longitudinal and transverse baryonic acoustic oscillation (BAO) scale from the anisotropic power spectrum signal inferred from 377 458 galaxies between redshifts 0.6 and 1.0, with the effective redshift of zeff = 0.698 and effective comoving volume of 2.72 Gpc3. After applying reconstruction, we measure the BAO scale and infer DH(zeff)/rdrag = 19.30 ± 0.56 and DM(zeff)/rdrag = 17.86 ± 0.37. When we perform an RSD analysis on the pre-reconstructed catalogue on the monopole, quadrupole, and hexadecapole we find, DH(zeff)/rdrag = 20.18 ± 0.78, DM(zeff)/rdrag = 17.49 ± 0.52 and fσ8(zeff) = 0.454 ± 0.046. We combine both sets of results along with the measurements in configuration space and report the following consensus values: DH(zeff)/rdrag = 19.77 ± 0.47, DM(zeff)/rdrag = 17.65 ± 0.30 and fσ8(zeff) = 0.473 ± 0.044, which are in full agreement with the standard CDM and GR predictions. These results represent the most precise measurements within the redshift range 0.6 ≤ z ≤ 1.0 and are the culmination of more than 8 yr of SDSS observations

On the Evolutionary Modification of Self-Incompatibility: Implications of Partial Clonality for Allelic Diversity and Genealogical Structure

Experimental investigations of homomorphic self-incompatibility (SI) have revealed an unanticipated level of complexity in its expression, permitting fine regulation over the course of a lifetime or a range of environmental conditions. Many flowering plants express some level of clonal reproduction, and phylogenetic analyses suggest that clonality evolves in a correlated fashion with SI in Solanum (Solanaceae). Here, we use a diffusion approximation to explore the effects on the evolutionary dynamics of SI of vegetative propagation with SI restricted to reproduction through seed. While clonality reduces the strength of frequency-dependent selection maintaining S-allele diversity, much of the great depth typical of S-allele genealogies is preserved. Our results suggest that clonality can play an important role in the evolution of SI systems, and may afford insight into unexplained features of allele genealogies in the Solanaceae