In short, the main contributions of this paper are fourfold: (i) to employ unsupervised OPF for non-technical losses detection, (ii) to model the problem of NTL as being an anomaly detection task, (iii) to employ unsupervised OPF to estimate the parameters of the Gaussian distributions, and (iv) to present an anomaly detection approach based on unsupervised optimum-path forest.
This paper addresses the problem of urban scene monitoring and tracking of obstacles based on unsupervised, deep-learning approaches.
To this end, feedforward neural networks (FNNs) and a feature selection method based on unsupervised clustering, were employed.
According to the context and available data, it is based on unsupervised, supervised or semi-supervised algorithms [34].
Patients stratification based on unsupervised hierarchical clustering divided patients into two groups.
SOM, an artificial intelligence algorithm based on unsupervised learning configures output vectors into a topological presentation of the original data.
Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer.
We wish to explore an alternative analysis approach, based on unsupervised, nonlinear, topographic (structure-preserving) projection and visualisation methods.
To further examine these options, we subdivided all 549 observed expression profile into 12 clusters, based on unsupervised hierarchical clustering.
However, the existing alignment-free methods are all based on unsupervised learning strategy (e.g., PCA or hierarchical clustering).
