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ORCIDHenrik Boström
- > Home > Persons > Henrik Boström
Publications
- 2023
[c108]Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, Henrik Boström:
Confidence Classifiers with Guaranteed Accuracy or Precision. COPA 2023: 513-533- [c107]Tuwe Löfström, Alexander Bondaletov, Artem Ryasik, Henrik Boström, Ulf Johansson:
Tutorial on using Conformal Predictive Systems in KNIME. COPA 2023: 602-620 - 2022
- [j26]Ulf Johansson, Cecilia Sönströd, Tuwe Löfström
, Henrik Boström:
Rule extraction with guarantees from regression models. Pattern Recognit. 126: 108554 (2022) - 2021
- [c101]Henrik Boström, Ulf Johansson, Tuwe Löfström:
Mondrian conformal predictive distributions. COPA 2021: 24-38 - [c100]Ulf Johansson, Tuwe Löfström, Henrik Boström:
Calibrating multi-class models. COPA 2021: 111-130 - [c98]Ulf Johansson, Tuwe Löfström, Henrik Boström:
Well-Calibrated and Sharp Interpretable Multi-Class Models. MDAI 2021: 193-204 - [c97]Ulf Johansson, Henrik Boström, Tuwe Löfström:
Investigating Normalized Conformal Regressors. SSCI 2021: 1-8 - 2019
- [j20]Ulf Johansson, Tuve Löfström, Henrik Linusson, Henrik Boström:
Efficient Venn predictors using random forests. Mach. Learn. 108(3): 535-550 (2019) - [c90]Ulf Johansson, Tuwe Löfström, Henrik Boström, Cecilia Sönströd:
Interpretable and specialized conformal predictors. COPA 2019: 3-22 - [c88]Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, Henrik Boström:
Customized Interpretable Conformal Regressors. DSAA 2019: 221-230 - [c87]Ulf Johansson, Tuwe Löfström, Henrik Boström:
Calibrating Probability Estimation Trees using Venn-Abers Predictors. SDM 2019: 28-36 - 2018
- [j19]Ulf Johansson, Henrik Linusson, Tuve Löfström, Henrik Boström:
Interpretable regression trees using conformal prediction. Expert Syst. Appl. 97: 394-404 (2018) - [c85]Ulf Johansson, Tuwe Löfström, Håkan Sundell, Henrik Linusson, Anders Gidenstam, Henrik Boström:
Venn predictors for well-calibrated probability estimation trees. COPA 2018: 3-14 - [c84]Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström:
Classification with Reject Option Using Conformal Prediction. PAKDD (1) 2018: 94-105 - 2017
- [j18]Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Johansson:
Accelerating difficulty estimation for conformal regression forests. Ann. Math. Artif. Intell. 81(1-2): 125-144 (2017) - [c82]Henrik Linusson, Ulf Norinder, Henrik Boström, Ulf Johansson, Tuve Löfström:
On the Calibration of Aggregated Conformal Predictors. COPA 2017: 154-173 - [c81]Ernst Ahlberg, Susanne Winiwarter, Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Norinder, Ulf Johansson, Ola Engkvist, Oscar Hammar, Claus Bendtsen, Lars Carlsson:
Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. COPA 2017: 174-184 - [c79]Ulf Johansson, Henrik Linusson, Tuve Löfström, Henrik Boström:
Model-agnostic nonconformity functions for conformal classification. IJCNN 2017: 2072-2079 - 2016
- [c76]Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Johansson:
Evaluation of a Variance-Based Nonconformity Measure for Regression Forests. COPA 2016: 75-89 - [c72]Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström:
Reliable Confidence Predictions Using Conformal Prediction. PAKDD (1) 2016: 77-88 - 2015
- [j13]Tuve Löfström, Henrik Boström, Henrik Linusson, Ulf Johansson:
Bias reduction through conditional conformal prediction. Intell. Data Anal. 19(6): 1355-1375 (2015) - 2014
- [j9]Ulf Johansson, Henrik Boström, Tuve Löfström, Henrik Linusson:
Regression conformal prediction with random forests. Mach. Learn. 97(1-2): 155-176 (2014) - [c58]Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström:
Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers. AIAI Workshops 2014: 261-270 - [c57]Ulf Johansson, Rikard König, Henrik Linusson, Tuve Löfström, Henrik Boström:
Rule Extraction with Guaranteed Fidelity. AIAI Workshops 2014: 281-290 - 2013
- [c52]Ulf Johansson, Rikard König, Tuve Löfström, Henrik Boström:
Evolved decision trees as conformal predictors. IEEE Congress on Evolutionary Computation 2013: 1794-1801 - [c51]Ulf Johansson, Tuve Löfström, Henrik Boström:
Overproduce-and-select: The grim reality. CIEL 2013: 52-59 - [c50]Ulf Johansson, Henrik Boström, Tuve Löfström:
Conformal Prediction Using Decision Trees. ICDM 2013: 330-339 - [c49]Ulf Johansson, Tuve Löfström, Henrik Boström:
Random brains. IJCNN 2013: 1-8 - [c48]Tuve Löfström, Ulf Johansson, Henrik Boström:
Effective utilization of data in inductive conformal prediction using ensembles of neural networks. IJCNN 2013: 1-8 - 2012
- [j7]Ulf Johansson, Cecilia Sönströd, Tuve Löfström, Henrik Boström:
Obtaining accurate and comprehensible classifiers using oracle coaching. Intell. Data Anal. 16(2): 247-263 (2012) - 2010
- [c41]Tuve Löfström, Ulf Johansson, Henrik Boström:
Comparing methods for generating diverse ensembles of artificial neural networks. IJCNN 2010: 1-6 - 2009
- [c39]Tuve Löfström, Ulf Johansson, Henrik Boström:
Ensemble member selection using multi-objective optimization. CIDM 2009: 245-251 - 2008
- [c31]Tuve Löfström, Ulf Johansson, Henrik Boström:
On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. ICMLA 2008: 127-132 - [c29]Ulf Johansson, Tuve Löfström, Henrik Boström:
The problem with ranking ensembles based on training or validation performance. IJCNN 2008: 3222-3228 - [c27]Ulf Johansson, Cecilia Sönströd, Tuve Löfström, Henrik Boström:
Chipper - A Novel Algorithm for Concept Description. SCAI 2008: 133-140
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last updated on 2024-09-23 23:27 CEST by the dblp team
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