Year: 2017
Type: conference-paper
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.
Source: Lirias
Authors: Verbruggen, Gust, De Raedt, Luc
Institution: KU Leuven
Language: English
Topic: Data Quality and Management
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2762498395