Sumanth_M_N07 / MPU6500_IMU Public

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

Test data

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Sample name	Expected outcome	Length	Accuracy	Result
testing.6v8n4n9v	testing	195ms			Show classification Show in data acquisition Show in feature explorer
testing.6v8n3qad	testing	195ms			Show classification Show in data acquisition Show in feature explorer
testing.6v8mo847	testing	195ms		Front_and_Back	Show classification Show in data acquisition Show in feature explorer
testing.6v8mm7tl	testing	10s		50 Up_and_Down	Show classification Show in data acquisition Show in feature explorer
Accident.6up99blr	Accident	10s	94%	47 Accident, 2 uncertain, 1 Up_and_Down	Show classification Show in data acquisition Show in feature explorer
Accident.6up96iid	Accident	10s	94%	47 Accident, 2 uncertain, 1 Up_and_Down	Show classification Show in data acquisition Show in feature explorer
Accident.6up7toc1	Accident	10s	100%	50 Accident	Show classification Show in data acquisition Show in feature explorer
Accident.6up7q528	Accident	10s	100%	50 Accident	Show classification Show in data acquisition Show in feature explorer
Up_and_Down.6up7j1f3	Up_and_Down	10s	98%	49 Up_and_Down, 1 uncertain	Show classification Show in data acquisition Show in feature explorer
Up_and_Down.6up7igf8	Up_and_Down	10s	96%	48 Up_and_Down, 2 Accident	Show classification Show in data acquisition Show in feature explorer
Right_and_Left.6up5qtct	Right_and_Left	10s	100%	50 Right_and_Left	Show classification Show in data acquisition Show in feature explorer
Front_and_Back.6up5kk20	Front_and_Back	10s	100%	50 Front_and_Back	Show classification Show in data acquisition Show in feature explorer
Front_and_Back.6up5jnia	Front_and_Back	10s	100%	50 Front_and_Back	Show classification Show in data acquisition Show in feature explorer
Front_and_Back.6up5j5ok	Front_and_Back	10s	100%	50 Front_and_Back	Show classification Show in data acquisition Show in feature explorer
Idle.6up5ca28	Idle	10s	100%	50 Idle	Show classification Show in data acquisition Show in feature explorer
Idle.6up573bg	Idle	10s	100%	50 Idle	Show classification Show in data acquisition Show in feature explorer

Model testing output

Results

Accuracy

98.50%

Metrics for Classifier

Metric	Value
Area under ROC Curve	1.00
Weighted average Precision	0.99
Weighted average Recall	0.99
Weighted average F1 score	0.99

Confusion matrix

Feature explorer

Every learning block has a threshold. This can be the minimum confidence that a neural network needs to have, or the maximum anomaly score before a sample is tagged as an anomaly. You can configure these thresholds to tweak the sensitivity of these learning blocks. This affects both live classification and model testing.

Classifier

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	S Sumanth_M_N07

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Test data

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