Titlebook: Machine Learning and Knowledge Extraction; Third IFIP TC 5, TC Andreas Holzinger,Peter Kieseberg,Edgar Weippl Conference proceedings 2019

BET

Machine Learning and Knowledge Extraction978-3-030-29726-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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CRACY

KANDINSKY Patterns as IQ-Test for Machine Learning,idation and training of explainability in AI. Kandinsky Patterns are at the same time easily distinguishable from human observers. Consequently, controlled patterns can be described by . humans and computers. The results of our study show that the majority of human explanations was made based on the

Initiative

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Estimating the Driver Status Using Long Short Term Memory,ituations and warn the drivers. We conducted an experiment in eight different driving scenarios and collected a large dataset from driving data and driver related data. We chose Long Short Term Memory (LSTM) as our machine learning method. We built and trained a stacked LSTM network to estimate the

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Using Relational Concept Networks for Explainable Decision Support, steer the interpretation of the little data available with the knowledge of the expert..We created a framework that consists of concepts and relations between those concepts, for which the exact relational importance is not necessarily specified. A machine-learning approach is used to determine the

神經(jīng)

破裂

Hot-Flash

Ranked MSD: A New Feature Ranking and Feature Selection Approach for Biomarker Identification,, we have developed a new algorithm for feature ranking and feature selection, named .. We have tested our proposed approach on two real-world gene expression data sets, both of which relate to respiratory viral infections. This Ranked MSD feature selection algorithm is able to reduce the feature se

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How to Improve the Adaptation Phase of the CBR in the Medical Domain,s very different from the stored ones, so the input from participated experts is needed, and a new rule will be stored. (3) The new case is partially similar satisfying adaptability conditions, in such a situation we adopt related decision rule to the new conditions under the supervision of the expe