[Industrial Solutions Guide] - AC Motor Fault Detection - LGBM Random Forest

Edge Impulse Inc. / [Industrial Solutions Guide] - AC Motor Fault Detection Public

Target: Nordic nRF5340 DK (Cortex-M33 128MHz) Clone this project

LGBM Random Forest settings

Training settings

Training processor

Please provide a valid training processor option

Number of boosting iterations

Number of boosting iterations should be a number

Max. depth

Max. depth should be a number

Advanced training settings

Validation set size

Please provide a valid number for the train/validate split (between 0 and 1)

Split train/validation set on metadata key

Profile int8 model

Neural network architecture

Save

Input layer (152 features)

LGBM Random Forest

Output layer (11 classes)

Model

Model version:

Last training performance (validation set)

Accuracy

95.6%

Loss

0.18

Confusion matrix (validation set)

Data explorer (full training set)

On-device performance

Engine:

Inferencing time

11 ms.

Peak RAM usage

1.5K

Flash usage

311.2K

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

	Name
	Zin Edge Impulse staff
	Ivan Turasov Edge Impulse staff
	KP Kinara Pandya Edge Impulse staff
	markwaters Edge Impulse staff