ENBIS Spring Meeting 2024

Session

Contributed session

15 May 2024, 15:30

Dortmund

Conveners

Contributed session: 2

• Antonio Lepore (Università degli Studi di Napoli Federico II - Dept. of Industrial Engineering)

39. Methods for Quantifying Dataset Similarity: a Review, Taxonomy and Comparison

Marieke Stolte (Department of Statistics, TU Dortmund University)

15/05/2024, 15:30

Spring Meeting

Quantifying the similarity between datasets has widespread applications in statistics and machine learning. The performance of a predictive model on novel datasets, referred to as generalizability, depends on how similar the training and evaluation datasets are. Exploiting or transferring insights between similar datasets is a key aspect of meta-learning and transfer-learning. In simulation...

45. Explanation Groves – Analyzing the Trade-off between Complexity and Adequacy of an Explanation

Gero Szepannek (Stralsund University of Applied Sciences)

15/05/2024, 15:50

Spring Meeting

The increasing popularity of machine learning in many application fields has led to an increasing demand in methods of explainable machine learning as they are e.g. provided by the R packages DALEX (Biecek, 2018) and iml (Molnar, 2018). A general process to ensure the development of transparent and auditable machine learning models in industry (TAX4CS) is given in Bücker et al. (2021).

In...

46. Quality aspects of machine learning in official statistics

Florian Dumpert (Federal Statistical Office of Germany)

15/05/2024, 16:10

Spring Meeting

Advanced statistical and machine learning models methods are becoming increasingly important in applied data science. At the same time, their trustworthiness is critical for the progress and adoption of data science applications in various fields, including official statistics.

„Bad quality reduces trust very, very fast.“ Taking up this dictum, official statistics in Germany have...