Bootstrap Sampling Based Data Cleaning and Maximum Entropy SVMs for Large Datasets

This chapter highlights the methodologies which are increasingly being applied to large datasets or ‘big data’, with an emphasis on bio-informatics. The first stage of any analysis is to collect data from a well-designed study. The chapter begins by looking at the raw data that arises from epidemiological studies and highlighting the first stages in creating clean data that can be used to draw informative conclusions through analysis. The remainder of the chapter covers data formats, data exploration, data cleaning, missing data (i.e. the lack of data for a variable in an observation), reproducibility, classification versus regression, feature identification and selection, method selection (e.g. supervised versus unsupervised machine learning), training a classifier, and drawing conclusions from modelling.

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IntelliClean: A Teaching Case Designed to Integrate Data Cleaning and Spreadsheet Skills into the Audit Curriculum

Journal of Emerging Technologies in Accounting ◽

10.2308/jeta-2020-025 ◽

2020 ◽

Vol 17 (2) ◽

pp. 17-24

Author(s):

Kara Hunter ◽

Cristina T. Alberti ◽

Scott R. Boss ◽

Jay C. Thibodeau

Keyword(s):

Data Cleaning ◽

Private Universities ◽

Large Datasets ◽

Learning Objectives ◽

Cleaning Process ◽

Case Assignment ◽

Teaching Case ◽

Auditing Standards ◽

Electronic Spreadsheet ◽

Integrate Data

ABSTRACT This teaching case provides an approach for educators to impart knowledge about both the data-cleaning process and critical electronic spreadsheet functionalities that are used by auditors to students as part of the auditing curriculum. The cleaning of large datasets has become a vital task that is routinely performed by the most junior audit professional on the team. In this case, students learn how to cleanse a dataset and verify the completeness and accuracy of the dataset in accordance with relevant auditing standards. Importantly, all steps are completed on an author-created database within an electronic spreadsheet platform. The response from students has been strong. After completing the case assignment, a total of 81 auditing students at two private universities provided feedback. The results of the questionnaire reveal that students largely agree that the key learning objectives were achieved, validating the use of this case in the auditing curriculum.

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DATA PREPARATION ON LARGE DATASETS FOR DATA SCIENCE

Asian Journal of Pharmaceutical and Clinical Research ◽

10.22159/ajpcr.2017.v10s1.20526 ◽

2017 ◽

Vol 10 (13) ◽

pp. 485

Author(s):

Darshan Barapatre ◽

Vijayalakshmi A

Keyword(s):

Machine Learning ◽

Data Science ◽

Data Cleaning ◽

Large Datasets ◽

Machine Learning Algorithms ◽

Unstructured Data ◽

Data Preparation ◽

Data Profiling ◽

Data Scientist ◽

Preparation Techniques

According to interviews and experts, data scientists spend 50-80% of the valuable time in the mundane task of collecting and preparing structured or unstructured data, before it can be explored for useful analysis. It is very valuable for a data scientist to restructure and refine the data into more meaningful datasets, which can be used further for analytics. Hence, the idea is to build a tool which will contain all the required data preparation techniques to make data well-structured by providing greater flexibility and easy to use UI. Tool will contain different data preparation techniques which will include the process of data cleaning, data structuring, transforming data, data compression, and data profiling and implementation of related machine learning algorithms.

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Stochasting modeling of planetary ring systems

International Astronomical Union Colloquium ◽

10.1017/s025292110010154x ◽

1984 ◽

Vol 75 ◽

pp. 461-469 ◽

Cited By ~ 1

Author(s):

Robert W. Hart

Keyword(s):

Maximum Entropy ◽

Ring System ◽

The Sun ◽

Ultimate State ◽

Interparticle Interactions ◽

Ring Systems ◽

First Order ◽

Planetary Ring ◽

Insight Into

ABSTRACTThis paper models maximum entropy configurations of idealized gravitational ring systems. Such configurations are of interest because systems generally evolve toward an ultimate state of maximum randomness. For simplicity, attention is confined to ultimate states for which interparticle interactions are no longer of first order importance. The planets, in their orbits about the sun, are one example of such a ring system. The extent to which the present approximation yields insight into ring systems such as Saturn's is explored briefly.

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