Mirka Saarela
Cited by
Cited by
Comparison of feature importance measures as explanations for classification models
M Saarela, S Jauhiainen
SN Applied Sciences 3 (2), 272, 2021
Learning Analytics: Fundaments, Applications, and Trends
A Peña-Ayala, P Leitner, M Saarela, S Sergis, JJ Vie, DYT Liu, L Vigentini, ...
Springer International Publishing, 2017
Analysing student performance using sparse data of core bachelor courses
M Saarela, T Kärkkäinen
JEDM-Journal of Educational Data Mining 7 (1), 3-32, 2015
Expert-based versus citation-based ranking of scholarly and scientific publication channels
M Saarela, T Kärkkäinen, T Lahtonen, T Rossi
Journal of Informetrics 10 (3), 693-718, 2016
Predicting hospital associated disability from imbalanced data using supervised learning
M Saarela, OP Ryynänen, S Äyrämö
Artificial Intelligence in Medicine 95, 88-95, 2019
Can we automate expert-based journal rankings? Analysis of the Finnish publication indicator
M Saarela, T Kärkkäinen
Journal of Informetrics 14 (2), 101008, 2020
Discovering gender-specific knowledge from Finnish basic education using PISA scale indices
M Saarela, T Kärkkäinen
International Conference on Educational Data Mining, 60-67, 2014
Analysing the Nigerian Teacher's Readiness for Technology Integration.
E Ifinedo, M Saarela, T Hämälänen
International Journal of Education and Development using Information and …, 2019
Knowledge discovery from the programme for international student assessment
M Saarela, T Kärkkäinen
Learning Analytics: Fundaments, Applications, and Trends: A View of the …, 2017
Predicting math performance from raw large-scale educational assessments data: a machine learning approach
M Saarela, B Yener, MJ Zaki, T Kärkkäinen
JMLR workshop and conference proceedings, 2016
Explainable student agency analytics
M Saarela, V Heilala, P Jääskelä, A Rantakaulio, T Kärkkäinen
IEEE Access 9, 137444-137459, 2021
Robustness, stability, and fidelity of explanations for a deep skin cancer classification model
M Saarela, L Geogieva
Applied Sciences 12 (19), 9545, 2022
Robust principal component analysis of data with missing values
T Kärkkäinen, M Saarela
International Conference on Machine Learning and Data Mining in Pattern …, 2015
Do Country Stereotypes Exist in PISA? A Clustering Approach for Large, Sparse, and Weighted Data.
M Saarela, T Kärkkäinen
International Conference on Educational Data Mining, 156--163, 2015
Course satisfaction in engineering education through the lens of student agency analytics
V Heilala, M Saarela, P Jääskelä, T Kärkkäinen
2020 IEEE Frontiers in Education Conference (FIE), 1-9, 2020
Feature Ranking of Large, Robust, and Weighted Clustering Result
M Saarela, J Hämäläinen, T Kärkkäinen
21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data …, 2017
Understanding the study experiences of students in low agency profile: Towards a smart education approach
V Heilala, P Jääskelä, T Kärkkäinen, M Saarela
International conference on smart Information & communication Technologies …, 2019
Weighted clustering of sparse educational data
M Saarela, T Kärkkäinen
Proceedings of the European Symposium on Artificial Neural Networks …, 2015
The Finnish version of the affinity for technology interaction (ATI) scale: psychometric properties and an examination of gender differences
V Heilala, R Kelly, M Saarela, P Jääskelä, T Kärkkäinen
International Journal of Human–Computer Interaction 39 (4), 874-892, 2023
Automatic knowledge discovery from sparse and large-scale educational data: case Finland
M Saarela
Jyväskylä studies in computing, 2017
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