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- W1554944210 abstract "ELKI is a unified software framework, designed as a tool suitable for evaluation of different algorithms on high dimensional real-valued feature-vectors. A special case of high dimensional real-valued feature-vectors are time series data where traditional distance measures like L p -distances can be applied. However, also a broad range of specialized distance measures like, e.g., dynamic time-warping, or generalized distance measures like second order distances, e.g., shared-nearest-neighbor distances, have been proposed. The new version ELKI 0.2 now is extended to time series data and offers a selection of these distance measures. It can serve as a visualization- and evaluation-tool for the behavior of different distance measures on time series data." @default.
- W1554944210 created "2016-06-24" @default.
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- W1554944210 date "2009-01-01" @default.
- W1554944210 modified "2023-10-16" @default.
- W1554944210 title "ELKI in Time: ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series" @default.
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- W1554944210 doi "https://doi.org/10.1007/978-3-642-02982-0_35" @default.
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