Expert Network HR Org / Heart Rate Analysis Public

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
stress_beef0c34-bf3a-4c21-8678-9be4aad1e1b1	stress	8m 0s	92%	11 stress, 1 working	Show classification Show in data acquisition Show in feature explorer
stress_dcdad8e7-56c6-47b7-a79e-7824da6be125	stress	4m 0s	100%	6 stress	Show classification Show in data acquisition Show in feature explorer

Model testing output

Results

Accuracy

94.44%

Metrics for Classifier

Metric	Value
Weighted average Precision	1.00
Weighted average Recall	0.94
Weighted average F1 score	0.97

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

Minimum confidence rating

Should be numeric

These users will be notified over email when this job finishes.

	Name
	AlexE Edge Impulse staff
	Roni Bandini
	David Tischler Edge Impulse staff
	D Dmitry Edge Impulse staff

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Target device

Define your target device requirements to inform model optimizations and performance calculations. No device yet? Use the default settings which you can change at any time.

Target device

Processor family

Clock rate

| MHz

Max

Custom device name

Application budget

Specify the available RAM and ROM for the model's operation, along with the maximum allowed latency for your specific application. Not sure yet? Start with the defaults and modify them later on.

RAM

| KB

Max

ROM

| KB

Max

Latency

| ms

Max

YEARLY

$400 /month

billed annually

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MONTHLY

$475 /month

billed monthly

Test data

Model variants