| 1. |
- De Raedt, Luc, 1964-, et al.
(författare)
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Elements of an Automatic Data Scientist
- 2018
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Ingår i: Advances in Intelligent Data Analysis XVII. - Cham : Springer International Publishing. - 9783030017675 - 9783030017682
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Konferensbidrag (refereegranskat)abstract
- A simple but non-trivial setting for automating data science is introduced. Given are a set of worksheets in a spreadsheet and the goal is to automatically complete some values. We also outline elements of the Synth framework that tackles this task: Synth-a-Sizer, an automated data wrangling system for automatically transforming the problem into attribute-value format; TacLe, an inductive constraint learning system for inducing formulas in spreadsheets; Mercs, a versatile predictive learning system; as well as the autocompletion component that integrates these systems.
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| 2. |
- Jordan, Kelsey, et al.
(författare)
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EULAR Recommendations 2003: an evidence based approach to the management of knee osteoarthritis: Report of a Task Force of the Standing Committee for International Clinical Studies Including Therapeutic Trials (ESCISIT)
- 2003
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 62:12, s. 1145-1155
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To update the EULAR recommendations for management of knee osteoarthritis (OA) by an evidence based medicine and expert opinion approach. Methods: The literature search and guidelines were restricted to treatments for knee OA pertaining to clinical and/or radiological OA of any compartment of the knee. Papers for combined treatment of knee and other types of OA were excluded. Medline and Embase were searched using a combination of subject headings and key words. Searches for those treatments previously investigated were conducted for January 1999 to February 2002 and for those treatments not previously investigated for 1966 to February 2002. The level of evidence found for each treatment was documented. Quality scores were determined for each paper, an effect size comparing the treatment with placebo was calculated, where possible, and a toxicity profile was determined for each treatment modality. Results: 497 new publications were identified by the search. Of these, 103 were intervention trials and included in the overall analysis, and 33 treatment modalities were identified. Previously identified publications which were not exclusively knee OA in the initial analysis were rejected. In total, 545 publications were included. Based on the results of the literature search and expert opinion, 10 recommendations for the treatment of knee OA were devised using a five stage Delphi technique. Based on expert opinion, a further set of 10 items was identified by a five stage Delphi technique as important for future research. Conclusion: The updated recommendations support some of the previous propositions published in 2000 but also include modified statements and new propositions. Although a large number of treatment options for knee OA exist, the evidence based format of the EULAR Recommendations continues to identify key clinical questions that currently are unanswered.
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| 3. |
- Verbruggen, Gust, et al.
(författare)
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Automatically Wrangling Spreadsheets into Machine Learning Data Formats
- 2018
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Ingår i: Advances in Intelligent Data Analysis XVII. - Cham : Springer. - 9783030017675 - 9783030017682 ; , s. 367-379
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Konferensbidrag (refereegranskat)abstract
- To help automate the important pre-processing step in machine learning and data mining, we introduce synth-a-sizer, a tool for semi-automatically wrangling spreadsheets into attribute-value format, so that they can be used by popular machine learning tools, only requiring the user to mark cells belonging to one single example. synth-a-sizer is based on inductive programming principles. We introduce synth-a-sizer’s transformations, search algorithm as well as a heuristic and distance measure for identifying types. We also report on a first experimental evaluation.
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| 4. |
- Verbruggen, Gust, et al.
(författare)
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Towards automated relational data wrangling
- 2017
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Ingår i: Proceedings of AutoML2017 @ ECML-PKDD: Automatic selection, configuration and composition of machine learning algorithms. - : Technical University of Aachen. ; , s. 18-26
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Konferensbidrag (refereegranskat)abstract
- It is well-known in data science that 80% of the work is devoted to preprocessing and only 20% to the actual machine learning or data mining step. This motivates us to explore different ways to (help) automate that preprocessing step. This note focusses on the question whether it is possible to (help) automate the data wrangling process for tabular data in data science.
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