30 citations · 110 across the 11 of their papers we have counts for
3 papers · 1 filter
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
Pedram Daee, Tomi Peltola, Aki Vehtari +1
In human-in-the-loop machine learning, the user provides information beyond that in the training data. Many algorithms and user interfaces have been designed to optimize and facili…
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder +6
Predicting the efficacy of a drug for a given individual, using high-dimensional genomic measurements, is at the core of precision medicine. However, identifying features on which…
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
Luana Micallef, Iiris Sundin, Pekka Marttinen +5
Providing accurate predictions is challenging for machine learning algorithms when the number of features is larger than the number of samples in the data. Prior knowledge can impr…