Edge Impulse Inc. / LGBM Random Forest Classification Public

Target: Cortex-M7 216MHz Clone this project

Welcome to Edge Impulse, the largest community of edge AI developers!
This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.

LGBM Random Forest Classification

Accelerometer

About this project

This public Edge Impulse project does not have a README yet. Clone this project to add new data or retrain this project, or to deploy this project to a device.

Data (223 samples)

View all

updown.1jtamav3.ingestion-6c5775b99d-t9mll

ID: 846161562

Label: updown

Sample length: 3s

updown.1.vnjco7g

ID: 846161572

Label: updown

Sample length: 5s

updown.updown5.rsi2jle

ID: 846161524

Label: updown

Sample length: 10s

updown.updown2.rsi2j3p

ID: 846161527

Label: updown

Sample length: 10s

wave.testing.1.10ngrtpn

ID: 846161508

Label: wave

Sample length: 10s

idle.idle0.rsi2cgq

ID: 846161635

Label: idle

Sample length: 10s

updown.2.14l2b7r6

ID: 846161542

Label: updown

Sample length: 5s

updown.1tc0oihc.ingestion-5bb95d8b88-fc8nn

ID: 846161555

Label: updown

Sample length: 3s

Model accuracy (Unoptimized (float32))

Validation set

99.5%

Test set

96.4%

On-device performance (Cortex-M7 216MHz, Unoptimized (float32))

Latency

6 ms.

Peak RAM usage

5.5K

Flash usage

38.1K

Run this model

Scan QR code or launch in browser

Launch in browser

Dataset summary

Data collected

23m 21s

Sensors

accX, accY, accZ @ 62.5Hz

Labels

drink, fistbump, idle, snake, updown, wave

Project info

Project ID	245576
Project version	3
License	BSD 3-Clause Clear
No. of views	48,038
No. of clones	17