High-dimensional data exception detection system and method
A high-dimensional data and anomaly detection technology, which is applied in the field of high-dimensional data anomaly detection system, can solve problems such as slowing down, increasing data analysis time, and insufficient time to achieve absolute security, accurate anomaly detection, and high accuracy.
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Embodiment 1
[0050] see figure 1 , the present invention provides a high-dimensional data anomaly detection method, the original high-dimensional data anomaly detection method includes the following steps:
[0051] 1) Preprocessing the original high-dimensional data to remove the interference value in the original high-dimensional data, and filling the data after removing the interference value;
[0052] 2) Normalize the filled data;
[0053] 3) Dimensionality reduction is performed on the normalized data;
[0054] 4) Reshape the dimensionally reduced data to obtain supervised data;
[0055] 5) Using LSTM network to analyze the supervised data to obtain prediction data;
[0056] 6) Comparing the predicted data with real data to determine whether the original high-dimensional data is abnormal.
[0057] In step 1), see figure 1 In the S1 step, the original high-dimensional data is preprocessed to remove the interference value in the original high-dimensional data, and the data after the...
Embodiment 2
[0089] see figure 2 , the present invention also provides a high-dimensional data anomaly detection system, the high-dimensional data anomaly detection system includes: a preprocessing module 1, the preprocessing module 1 is used to preprocess the original high-dimensional data, to remove the The interference value in the original high-dimensional data, and the data after removing the interference value is filled; the normalization processing module 2, the normalization processing module 2 is connected with the preprocessing module 1, and the normalization processing module 2 is connected with the preprocessing module 1, and the A normalization processing module 2 is used for normalizing the filled data; a dimension reduction processing module 3, the dimension reduction processing module 3 is connected with the normalization processing module 2, and the dimension reduction processing module 3 For reducing the dimensionality of the normalized data; shaping processing module 4,...
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