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Found 7 papers, 2 papers with code
ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
\texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data.
SANGEA: Scalable and Attributed Network Generation
In this paper, we present SANGEA, a sizeable synthetic graph generation framework which extends the applicability of any SGG to large graphs.
Open challenges for Machine Learning based Early Decision-Making research
However, the later a decision is made, the more its accuracy tends to improve, since the description of the problem to hand is enriched over time.
When to Classify Events in Open Times Series?
In the Early Classification in Open Time Series problem (ECOTS), the task is to predict events, i. e. their class and time interval, at the moment that optimizes the accuracy vs. earliness trade-off.
Early and Revocable Time Series Classification
Many approaches have been proposed for early classification of time series in light of itssignificance in a wide range of applications including healthcare, transportation and fi-nance.
Early Classification of Time Series is Meaningful
Many approaches have been proposed for early classification of time series in light of its significance in a wide range of applications including healthcare, transportation and finance.
Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms
An increasing number of applications require to recognize the class of an incoming time series as quickly as possible without unduly compromising the accuracy of the prediction.
