Search Results for author: Yves Rangoni

Found 2 papers, 0 papers with code

Neighborhood Features Help Detecting Non-Technical Losses in Big Data Sets

no code implementations4 Jul 2016 Patrick Glauner, Jorge Meira, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte

Using the neighborhood features instead of only analyzing the time series has resulted in appreciable results for Big Data sets for varying NTL proportions of 1%-90%.

Time Series Time Series Analysis

Large-Scale Detection of Non-Technical Losses in Imbalanced Data Sets

no code implementations26 Feb 2016 Patrick O. Glauner, Andre Boechat, Lautaro Dolberg, Radu State, Franck Bettinger, Yves Rangoni, Diogo Duarte

We believe that the considerations and observations made in this contribution are necessary for future smart meter research in order to report their effectiveness on imbalanced and large real world data sets.

Small Data Image Classification

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