AI-driven HVAC Fault Diagnosis (Audio) - Model testing

Edge Impulse Experts / AI-driven HVAC Fault Diagnosis (Audio) Public

Target: Cortex-M4F 80MHz Clone this project

This lists all test data. You can manage this data through Data acquisition.

Test data

Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.

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Sample name	Expected outcome	Length	Accuracy	Result
audio_defective__2024_05_28_10_56_25	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_defective__2024_05_28_10_56_22	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_defective__2024_05_28_10_56_18	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_defective__2024_05_28_10_56_12	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_defective__2024_05_28_10_56_08	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_defective__2024_05_28_10_56_15	defective	2s	100%	3 defective	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_32	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_28	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_22	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_26	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_16	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer
audio_normal__2024_05_28_10_55_19	normal	2s	100%	3 normal	Show classification Show in data acquisition Show in feature explorer

Model testing output

Results

Accuracy

100.00%

Metrics for Classifier

Metric	Value
Area under ROC Curve	1.00
Weighted average Precision	1.00
Weighted average Recall	1.00
Weighted average F1 score	1.00

Confusion matrix

Feature explorer

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	Name
	Kutluhan Aktar

Test data

Model variants