Time series classification
- Exploratory analysis
- Model retraining
- Azure ML
- Association rules
- Mixture model
- Data factory
Interactive system for multivariate time series data classification and anomaly detection on Azure ML platform
Our developers have designed and developed a system for Multivariate time series data classification and anomaly detection in the data measured over a long time period, as parameters corresponding to correct and incorrect system behavior. The user interface based on web services was realized using Azure ML as well.
The interface allows the users, who have no machine learning knowledge, to upload a new data, retrain the system and get the results of prediction and analysis in a user-friendly form.
The main concern of this task was a big load of data and parameters with a low number of labeled data for each of the classes, for one certain measurement period.
Therefore, the work was completed in a few steps:
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