Results 21 to 30 of about 244,877 (310)
Interpretable machine learning on metabolomics data reveals biomarkers for Parkinson’s disease [PDF]
, 2022 The use of machine learning (ML) with metabolomics provides opportunities for the early diagnosis of disease. However, the accuracy and extent of information obtained from ML and metabolomics can be limited owing to challenges associated with ...
J. Diana, Zhang +3 more
core +2 more sources
Explainable and Interpretable Anomaly Detection Models for Production Data
, 2022 Trusting a machine-learning model is a critical factor that will speed the spread of the fourth industrial revolution. Trust can be achieved by understanding how a model is making decisions. For white-box models, it is easy to “see” the model and examine
Zhang, Xiangliang +4 more
core +1 more source
Fast and accurate interpretation of workload classification model.
PLoS ONE, 2023 How can we interpret predictions of a workload classification model? A workload is a sequence of operations executed in DRAM, where each operation contains a command and an address.
Sooyeon Shim +5 more
doaj +2 more sources
Studies in Chinese Linguistics, 2015 The study of English once and twice yields evidence that each of them is actually a complex phrase containing two visible morphemes and one silent one. Neither is a simple lexical item.
Richard S. Kayne
doaj +1 more source
, 2015 Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes.
Kramer, Stefan +5 more
core +1 more source
Interpretable attribution assignment for octanol-water partition coefficient [PDF]
, 2023 With the increasing development of machine learning models, their credibility has become an important issue. In chemistry, attribution assignment is gaining relevance in designing molecules and debugging models.
Daisuke, Yokogawa, Kayo, Suda
core +2 more sources
Constructing Interpretable Decision Trees Using Parallel Coordinates
, 2020 The interest in interpretable models that are not only accurate but also understandable is rapidly increasing; often resulting in the machine-learning community turning to decision tree classifiers.
Hexel, René +2 more
core +1 more source
Simplivariate Models: Ideas and First Examples [PDF]
, 2008 One of the new expanding areas in functional genomics is metabolomics: measuring the metabolome of an organism. Data being generated in metabolomics studies are very diverse in nature depending on the design underlying the experiment.
Werf, M.J. van der +26 more
core +3 more sources
Interpretable and verifiable planning and prediction for autonomous vehicles [PDF]
, 2023 Autonomous driving (AD) has gained much attention in recent years due to its many potential benefits such as improving safety and increasing efficiency. However, AD is a difficult problem with challenges such as handling interactions with other vehicles ...
Brewitt, Cillian
core +1 more source
M@n@gement, 2022 Data we collect and use in organisation and management studies look like ‘cold cases’. We want to offer more conversations, interpretations, arguments and even disputes. The ‘Interpreters’ is a nexus where academics invite colleagues and friends to analyse and discuss freely an argument, raw data, cases and qualitative materials.
Pomiès, Anissa +3 more
openaire +4 more sources