Oct 15, 2019 � In this paper, a new shapelet discovery method, referred to as Pruning Shapelets with Key Points (PSKP), is proposed. PSKP first finds the key�...
In this paper, a new shapelet discovery method, referred to as Pruning Shapelets with Key Points (PSKP), is proposed. PSKP first finds the key points in time�...
In this paper, we will propose two novelty. First, we will improve the original key-points based shapelet discovery algorithm. Second, we will apply the�...
This paper will improve the original key-points based shapelet discovery algorithm and apply the improved novel concept to shapelet transform algorithm.
This paper proposes a novel shapelet learning method for time series classification. The proposed method uses a self-organizing incremental neural network to�...
We propose disconnecting the process of finding shapelets from the classification algorithm by proposing a shapelet transformation.
Time series shapelets are a recent promising concept in time series data mining. Shapelets are time series snippets that can be used to classify unlabeled time.
Instance Profile for Shapelet Discovery for Time Series Classification
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Time series shapelets (or simply, shapelets) are discriminative subsequences that have been recently found both effective and interpretable for solving TSC.
Shapelet distinguishes different categories by the local shape of the time series, has strong predictive ability and interpretability, and has received�...
Oct 24, 2020 � The efficiency of shapelet discovery is improved through a lazy strategy fusing global and local similarities.
