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

wave.0.11p6foah

ID: 846161518

Label: wave

Sample length: 5s

updown.1.vnjco7g

ID: 846161572

Label: updown

Sample length: 5s

wave.wave5.rsi2mjb

ID: 846161500

Label: wave

Sample length: 10s

idle.2.12bmqclq

ID: 846161637

Label: idle

Sample length: 5s

updown.1uj8vmqg.ingestion-6cfc94669f-mksp4

ID: 846161548

Label: updown

Sample length: 3s

updown.1tktb6q4.ingestion-99d59679d-l7kss

ID: 846161549

Label: updown

Sample length: 3s

fistbump.0.12blfu6d

ID: 846161654

Label: fistbump

Sample length: 5s

fistbump.6.12blm560

ID: 846161647

Label: fistbump

Sample length: 5s

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	40,177
No. of clones	15