Improved Weighted Random Forest for Classification Problems

Several studies have shown that combining machine learning models in an appropriate way will introduce improvements in the individual predictions made by the base models. The key to make well-performing ensemble model is in the diversity of the base models. Of the most common solutions for introducing diversity into the decision trees are bagging and random forest. Bagging enhances the diversity by sampling with replacement and generating many training data sets, while random forest adds selecting a random number of features as well. This has made the random forest a winning candidate for many machine learning applications. However, assuming equal weights for all base decision trees does not seem reasonable as the randomization of sampling and input feature selection may lead to different levels of decision-making abilities across base decision trees. Therefore, we propose several algorithms that intend to modify the weighting strategy of regular random forest and consequently make better predictions. The designed weighting frameworks include optimal weighted random forest based on ac-curacy, optimal weighted random forest based on the area under the curve (AUC), performance-based weighted random forest, and several stacking-based weighted random forest models. The numerical results show that the proposed models are able to introduce significant improvements compared to regular random forest

Análisis cultural de los ítems de dos listas de verificación quirúrgica de España y Argentina

Objective To compare the agreement between two surgical checklists implanted in two hospitals in Spain and Argentina, using the international classification for patient safety as a framework. Method This was an expert opinion study carried out using an ad hoc questionnaire in electronic format, which included 7 of the 13 categories of the international classification for patient safety. Fifteen surgical security experts from each country participated in this study by classifying the items on the checklists into the selected ICPS categories. The data were analyzed with SPSS V20 software. Results There was a greater percentage of classifications in fields related to the prevention of critical events. The category “clinical processes and procedures” was mentioned most frequently in both lists. Conclusion The implementation of the surgical safety checklist is variable. Experts considered that the Argentinian list was clearer in every dimension

Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles

Context: Demonstrating high reliability and safety for safety-critical systems (SCSs) remains a hard problem. Diverse evidence needs to be combined in a rigorous way: in particular, results of operational testing with other evidence from design and verification. Growing use of machine learning in SCSs, by precluding most established methods for gaining assurance, makes evidence from operational testing even more important for supporting safety and reliability claims. Objective: We revisit the problem of using operational testing to demonstrate high reliability. We use Autonomous Vehicles (AVs) as a current example. AVs are making their debut on public roads: methods for assessing whether an AV is safe enough are urgently needed. We demonstrate how to answer 5 questions that would arise in assessing an AV type, starting with those proposed by a highly-cited study. Method: We apply new theorems extending our Conservative Bayesian Inference (CBI) approach, which exploit the rigour of Bayesian methods while reducing the risk of involuntary misuse associated (we argue) with now-common applications of Bayesian inference; we define additional conditions needed for applying these methods to AVs. Results: Prior knowledge can bring substantial advantages if the AV design allows strong expectations of safety before road testing. We also show how naive attempts at conservative assessment may lead to over-optimism instead; why extrapolating the trend of disengagements (take-overs by human drivers) is not suitable for safety claims; use of knowledge that an AV has moved to a “less stressful” environment. Conclusion: While some reliability targets will remain too high to be practically verifiable, our CBI approach removes a major source of doubt: it allows use of prior knowledge without inducing dangerously optimistic biases. For certain ranges of required reliability and prior beliefs, CBI thus supports feasible, sound arguments. Useful conservative claims can be derived from limited prior knowledge

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Supplier selection based on evidence theory and analytic network process

© IMechE 2014. The supplier selection is a key component of the supply chain management. Existing methods for the supplier selection are based on analytic network process. They can handle the interdependence of decision attributes; however, these methods could not guarantee an optimal solution when given vague or incomplete input data. To deal with the uncertainties of input data, we propose methods combining analytic network process with Dempster'Shafer evidence theory. We demonstrate efficiency and accuracy of the proposed method in a numerical example. We demonstrate that the proposed method is flexible and effective in dealing with the supplier selection problem

Tephra layers of large explosive eruptions of Baitoushan/Changbaishan Volcano in the Japan Sea sediments

This paper is based on the results of a comprehensive investigations of sediments from seven cores sampled during the International Russian-Chinese Cruise 53 of the R/V “Akademik Lavrentyev” (2010) in the frames of the Russian-Chinese collaboration between the Pacific Oceanological Institute of the Far-Eastern Branch of the Russian Academy of Sciences (POI FEB RAS, Vladivostok, Russia), and the First Institute of Oceanography (FIO, Qingdao, China). Baitoushan (Chanbaishan) Volcano had several powerful explosive eruptions during the Middle Pleistocene-Holocene, which produced widespread tephra layers. The paper reports chemical composition of volcanic glasses and minerals from six tephra layers labeled as B-Og, B-Sado, B-J, B-Un1, B-V, and B-Tm, which belong to Baitoushan Volcano and were identified in sediments of the northwestern part of the Sea of Japan. The tephras were dated using geochronological data for the host sediments. The estimated ages for the Middle Pleistocene tephra is 488 ka; the Late Pleistocene tephras are 71.1–71.9 cal. kа (B-Sado), 50.8 cal. ka (B-J), 38.3 cal. ka (B-Un1), and 29.0–29.4 cal. ka (B-V). The ash layers consist of alkali-rich glass of trachydacitic to alkaline rhyolitic composition and specific assemblage of minerals including Fe-rich augite-hedenbergite, aegirine-augite, aegirine, arfvedsonite, and fayalite. The mineral assemblage is typical for alkalic volcanic rocks from continental rift setting. Aenigmatite, a rare mineral from the group of inosilicates, was firstly identified in distal tephra of Baitoushan Volcano, supplied into marine sediments. The composition of glasses and minerals from all layers are similar. It testifies about steady-state conditions of the magma accumulation under Baitoushan Volcano and about the bimodal character of magmatic chambers during the Late Pleistocene and Holocene (since 100 ka)