Explaining Support Vector Machines: A Color Based Nomogram.

PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models. OBJECTIVE: In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto) not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables. RESULTS: Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant). When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable. CONCLUSIONS: This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method

Random subwindows and extremely randomized trees for image classification in cell biology

Background: With the improvements in biosensors and high-throughput image acquisition technologies, life science laboratories are able to perform an increasing number of experiments that involve the generation of a large amount of images at different imaging modalities/scales. It stresses the need for computer vision methods that automate image classification tasks. Results: We illustrate the potential of our image classification method in cell biology by evaluating it on four datasets of images related to protein distributions or subcellular localizations, and red-blood cell shapes. Accuracy results are quite good without any specific pre-processing neither domain knowledge incorporation. The method is implemented in Java and available upon request for evaluation and research purpose. Conclusion: Our method is directly applicable to any image classification problems. We foresee the use of this automatic approach as a baseline method and first try on various biological image classification problems

Current trend in synthesis, Post-Synthetic modifications and biological applications of Nanometal-Organic frameworks (NMOFs)

Since the early reports of MOFs and their interesting properties, research involving these materials has grown wide in scope and applications. Various synthetic approaches have ensued in view of obtaining materials with optimised properties, the extensive scope of application spanning from energy, gas sorption, catalysis biological applications has meant exponentially evolved over the years. The far‐reaching synthetic and PSM approaches and porosity control possibilities have continued to serve as a motivation for research on these materials. With respect to the biological applications, MOFs have shown promise as good candidates in applications involving drug delivery, BioMOFs, sensing, imaging amongst others. Despite being a while away from successful entry into the market, observed results in sensing, drug delivery, and imaging put these materials on the spot light as candidates poised to usher in a revolution in biology. In this regard, this review article focuses current approaches in synthesis, post functionalization and biological applications of these materials with particular attention on drug delivery, imaging, sensing and BioMOFs

“A professor of darkness”: Higher Education and the Annihilation of Virtue in Cormac McCarthy's<i>The Sunset Limited</i>

AbstractWhile critics have remarked how The Sunset Limited stresses White's identity as a professor, they have had little to say regarding what this fact and White's suicidal longing reveal concerning McCarthy's view of the contemporary university. This article fills this gap by scrutinizing White's death wish through the lens of the academy's engagement with virtue. Drawing upon John Henry Newman's understanding of the relationship between the university and character formation, as well as traditional formulations of classical and Christian virtues, I show how White's arguments in favor of self-annihilation are grounded in an education lacking any pursuit of virtue of either kind. Representative of the modern academy, White has located all value not in an ethical consideration of how to be a good man in community with others, but in the artistic achievements of humanity; his vocation has concerned itself with aesthetics at the expense of virtue. Divorced especially from the theological virtues, the education White professes darkness by combining intellectual pride with moral skepticism in such a way as to subvert human solidarity, individual purpose, and indeed the project of the university itself.</jats:p

“When You Stop Pretending That You Know”

Abstract Increasingly addressing the religious dimension of Cormac McCarthy’s work, critics have frequently rooted it in a Gnosticism which holds, first, that the world is a place of evil and suffering and, second, that salvation is attained through knowledge made available only to the elect. The Stonemason, however, seems intent on refuting just such a thesis. Focusing on Ben and his grandfather Papaw, a centenarian stonemason, the play presents Ben as seeking, through mastery of the mason’s secrets, to become custodian to knowledge that will unlock the mysteries not just of a trade but of the cosmos. Yet this Gnostic quest fosters in him a moral negligence that leads to the deaths of two family members. Indeed, Ben’s tragedy stems precisely from his Gnostic prizing of secret lore and indifference to the Christian lessons Papaw himself most values—lessons not in god-like knowledge but in the practice of faith, humility, and love.</jats:p