ei_temperature_sensor - Anomaly detection

Zin / ei_temperature_sensor Public

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Anomaly detection settings

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temp Average

temp Minimum

temp Maximum

temp RMS

temp Stdev

temp Skewness

temp Kurtosis

Training output

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Model

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By definition there should be as few as possible anomalies in the training dataset, and thus accuracy is not calculated during training. Run Model testing to learn more about the model performance.

Anomaly explorer

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Y Axis

Test data

Retrain this model to reveal additional visualizations

Anomaly score

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Average axis distance

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Anomaly detection - Manage block versions

List of block versions ()

Note

To use an Input block version, connect it to a DSP block version using the Manage versions dialog on a DSP block page. The starred Input block version is the one connected to the Primary learn block, via a DSP block.

Note

To use a DSP block version, connect it to a Learn block version using the Manage versions dialog on a Learn block page. The starred DSP block version is the one connected to the Primary learn block.

Note

The Primary learn block version is the one that will be used when a project is deployed. When you set a Learn block version to Primary, any DSP and Input block versions it connects to will automatically be selected for deployment.

Selected version

Description

#23

Input blocks

Target device

Configure your target device for model performance calculations, and to enable target specific optimizations.

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Anomaly detection settings

Training output

Model

Anomaly explorer

Anomaly score

Average axis distance

Description

Last training performance (validation set)

Accuracy

Loss

Confusion matrix (validation set)

Feature explorer (full training set)

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Anomaly detection settings

Training output

Model

Anomaly explorer

Anomaly score

Average axis distance

Description

Last training performance (validation set)

Accuracy

Loss

Confusion matrix (validation set)

Feature explorer (full training set)

Settings