2,230 research outputs found
Hyperparameter Importance Across Datasets
With the advent of automated machine learning, automated hyperparameter
optimization methods are by now routinely used in data mining. However, this
progress is not yet matched by equal progress on automatic analyses that yield
information beyond performance-optimizing hyperparameter settings. In this
work, we aim to answer the following two questions: Given an algorithm, what
are generally its most important hyperparameters, and what are typically good
values for these? We present methodology and a framework to answer these
questions based on meta-learning across many datasets. We apply this
methodology using the experimental meta-data available on OpenML to determine
the most important hyperparameters of support vector machines, random forests
and Adaboost, and to infer priors for all their hyperparameters. The results,
obtained fully automatically, provide a quantitative basis to focus efforts in
both manual algorithm design and in automated hyperparameter optimization. The
conducted experiments confirm that the hyperparameters selected by the proposed
method are indeed the most important ones and that the obtained priors also
lead to statistically significant improvements in hyperparameter optimization.Comment: \c{opyright} 2018. Copyright is held by the owner/author(s).
Publication rights licensed to ACM. This is the author's version of the work.
It is posted here for your personal use, not for redistribution. The
definitive Version of Record was published in Proceedings of the 24th ACM
SIGKDD International Conference on Knowledge Discovery & Data Minin
Practical sand transport formula for non-breaking waves and currents
Open Access funded by Engineering and Physical Sciences Research Council Under a Creative Commons license Acknowledgements This work is part of the SANTOSS project (‘SANd Transport in OScillatory flows in the Sheet-flow regime’) funded by the UK's EPSRC (GR/T28089/01) and STW in The Netherlands (TCB.6586). JW acknowledges Deltares strategic research funding under project number 1202359.09. Richard Soulsby is gratefully acknowledged for valuable discussions and feedback on the formula during the SANTOSS project.Peer reviewedPostprin
High incidence of acute lung injury in children with Down syndrome
OBJECTIVE: Acute respiratory tract infection is a common reason for hospitalization in children with Down syndrome (CDS) and is characterized by a high morbidity. The severe course of disease in CDS may be related to a higher incidence of acute lung injury (ALI). This study evaluated the incidence of ALI and acute respiratory distress syndrome (ARDS) in mechanically ventilated CDS. DESIGN AND SETTING: Retrospective cohort study in a pediatric ICU. PATIENTS AND PARTICIPANTS: Cases were all mechanically ventilated CDS admitted to our unit between January 1998 and July 2005. All mechanically ventilated patients without Down syndrome from January 1998 to January 2001 served as controls. Postoperative patients (cases and controls) and those with a cardiac left to right shunt were excluded. MEASUREMENTS AND RESULTS: The main outcome measure was the incidence of ALI and ARDS. The criteria for ALI were met in 14 of 24 CDS (58.3%) in 41 of 317 of controls (12.9%; OR 9.4, 95% CI 3.9-22.6). The criteria for ARDS were met in 11 of 24 CDS (46%) and in 21 of 317 of controls (7%; OR 11.9, 95% CI 4.8-29.8). None of the CDS with ALI died; in the control group ten patients with ALI died. CONCLUSIONS: CDS had a significantly higher incidence of ALI and ARDS than children without Down syndrome. The explanation for this remains to be elucidated; further study is necessary before clinical implications become clea
Effectiveness of additional supervised exercises compared with conventional treatment alone in patients with acute lateral ankle sprains: systematic review
Objective To summarise the effectiveness of adding supervised exercises to conventional treatment compared with conventional treatment alone in patients with acute lateral ankle sprains
Single amino acid supplementation in aminoacidopathies:a systematic review
Aminoacidopathies are a group of rare and diverse disorders, caused by the deficiency of an enzyme or transporter involved in amino acid metabolism. For most aminoacidopathies, dietary management is the mainstay of treatment. Such treatment includes severe natural protein restriction, combined with protein substitution with all amino acids except the amino acids prior to the metabolic block and enriched with the amino acid that has become essential by the enzymatic defect. For some aminoacidopathies, supplementation of one or two amino acids, that have not become essential by the enzymatic defect, has been suggested. This so-called single amino acid supplementation can serve different treatment objectives, but evidence is limited. The aim of the present article is to provide a systematic review on the reasons for applications of single amino acid supplementation in aminoacidopathies treated with natural protein restriction and synthetic amino acid mixtures
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