Time sequence data classification method based on data feature fragments
A technology of data characteristics and time series, applied in database models, relational databases, electrical digital data processing, etc., can solve problems such as long training time, and achieve the effect of improving screening efficiency
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[0062]A method for classifying time series data based on data feature segments. This embodiment takes the world-recognized time series standard data set as an example (http: / / www.timeseriesclassification.com / ) to describe the corresponding implementation. The present invention selects the "Symbols" standard data set for detailed description of the processing steps. The training set of the "Symbols" data has 25 time series, each sequence length is 398, and the 25 sequences are divided into 6 categories. Such as figure 1 shown, including the following steps:
[0063] S1, preset data trend point selection rate ρ, selection quantity threshold of data feature segment Shapelets Num=1 / 2Num(D), data feature segment Shapelets quality evaluation standard is information gain (information gain), subclass division standard rate The corresponding subclass division standard rate μ is used in subsequent steps to complete the corresponding subclass division operation.
[0064] The selection...
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