Confusion Matrix Stability Bounds for Multiclass Classification

In this paper, we provide new theoretical results on the generalization properties of learning algorithms for multiclass classification problems. The originality of our work is that we propose to use the confusion matrix of a classifier as a measure of its quality; our contribution is in the line of work which attempts to set up and study the statistical properties of new evaluation measures such as, e.g. ROC curves. In the confusion-based learning framework we propose, we claim that a targetted objective is to minimize the size of the confusion matrix C, measured through its operator norm ||C||. We derive generalization bounds on the (size of the) confusion matrix in an extended framework of uniform stability, adapted to the case of matrix valued loss. Pivotal to our study is a very recent matrix concentration inequality that generalizes McDiarmid's inequality. As an illustration of the relevance of our theoretical results, we show how two SVM learning procedures can be proved to be confusion-friendly. To the best of our knowledge, the present paper is the first that focuses on the confusion matrix from a theoretical point of view

Annual modulation of the Galactic binary confusion noise bakground and LISA data analysis

We study the anisotropies of the Galactic confusion noise background and its effects on LISA data analysis. LISA has two data streams of the gravitational waves signals relevant for low frequency regime. Due to the anisotropies of the background, the matrix for their confusion noises has off-diagonal components and depends strongly on the orientation of the detector plane. We find that the sky-averaged confusion noise level $\sqrt {S(f)}$ could change by a factor of 2 in three months, and would be minimum when the orbital position of LISA is either around the spring or autumn equinox.Comment: 13 pages, 6 figure

Paradigm versus praxis: why psychology ‘absolute identification’ experiments do not reveal sensory processes

Purpose – A key cybernetics concept, information transmitted in a system, was quantified by Shannon. It quickly gained prominence, inspiring a version by Harvard psychologists Garner and Hake for “absolute identification” experiments. There, human subjects “categorize” sensory stimuli, affording “information transmitted” in perception. The Garner-Hake formulation has been in continuous use for 62 years, exerting enormous influence. But some experienced theorists and reviewers have criticized it as uninformative. They could not explain why, and were ignored. Here, the “why” is answered. The paper aims to discuss these issues. Design/methodology/approach – A key Shannon data-organizing tool is the confusion matrix. Its columns and rows are, respectively, labeled by “symbol sent” (event) and “symbol received” (outcome), such that matrix entries represent how often outcomes actually corresponded to events. Garner and Hake made their own version of the matrix, which deserves scrutiny, and is minutely examined here. Findings – The Garner-Hake confusion-matrix columns represent “stimulus categories”, ranges of some physical stimulus attribute (usually intensity), and its rows represent “response categories” of the subject’s identification of the attribute. The matrix entries thus show how often an identification empirically corresponds to an intensity, such that “outcomes” and “events” differ in kind (unlike Shannon’s). Obtaining a true “information transmitted” therefore requires stimulus categorizations to be converted to hypothetical evoking stimuli, achievable (in principle) by relating categorization to sensation to intensity. But those relations are actually unknown, perhaps unknowable. Originality/value – The author achieves an important understanding: why “absolute identification” experiments do not illuminate sensory processes

Neutrino Interactions in Octet Baryon Matter

Neutrino processes caused by the neutral current are studied in octet baryon matter. Previous confusion about the baryonic matrix elements of the neutral current interaction is excluded, and a correct table for them improved by consideration of the proton spin problem is presented instead.Comment: 6 page

Lattice Gauge Theory -- Present Status

Lattice gauge theory is our primary tool for the study of non-perturbative phenomena in hadronic physics. In addition to giving quantitative information on confinement, the approach is yielding first principles calculations of hadronic spectra and matrix elements. After years of confusion, there has been significant recent progress in understanding issues of chiral symmetry on the lattice. (Talk presented at HADRON 93, Como, Italy, June 1993.)Comment: 11 pages, BNL-4946

On non-abelian generalisation of Born-Infeld action in string theory

We show that the part of the tree-level open string effective action for the non-abelian vector field which depends on the field strength but not on its covariant derivatives, is given by the symmetrised trace of the direct non-abelian generalisation of the Born-Infeld invariant. We discuss applications to D-brane dynamics.Comment: 13 pages, harvmac. Some confusion about instanton matrix model solutions corrected (string solution is interpreted as a D-string bound to a large number of D-instantons