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2018
Conference Paper
Titel
Model-based data exploration
Abstract
Data exploration is an approach of visually exploring data in order to understand the characteristics of the dataset. As both size and complexity of datasets increase substantially, data scientists take less look at the data directly but conduct experiments by training models and assess the outcome when applying these models on test data. We denote the use of ML models to experimentally obtain insights into the data at hand as model-based data exploration and show some examples from a recent industrial project.