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Found 8 papers, 3 papers with code
A Survey and Implementation of Performance Metrics for Self-Organized Maps
Quantitative evaluation of self-organizing maps (SOM) is a subset of clustering validation, which is a challenging problem as such.
Selecting the Number of Clusters $K$ with a Stability Trade-off: an Internal Validation Criterion
In this perspective, clustering stability has emerged as a natural and model-agnostic principle: an algorithm should find stable structures in the data.
Deep Embedded SOM: Joint Representation Learning and Self-Organization
In the wake of recent advances in joint clustering and deep learning, we introduce the Deep Embedded Self-Organizing Map, a model that jointly learns representations and the code vectors of a self-organizing map.
Search Strategies for Binary Feature Selection for a Naive Bayes Classifier
We compare in this paper several feature selection methods for the Naive Bayes Classifier (NBC) when the data under study are described by a large number of redundant binary indicators.
Interpretable Aircraft Engine Diagnostic via Expert Indicator Aggregation
Detecting early signs of failures (anomalies) in complex systems is one of the main goal of preventive maintenance.
Anomaly Detection Based on Indicators Aggregation
Automatic anomaly detection is a major issue in various areas.
A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation
Aircraft engine manufacturers collect large amount of engine related data during flights.
Anomaly Detection Based on Aggregation of Indicators
Automatic anomaly detection is a major issue in various areas.
