Skip to content

Using Logistic Regression to train data from an accelerometer in order to recognize and categorize gestures. Key features: Using simple components like a microcontroller and deploying complex machine learning algorithms to obtain clean results.

Notifications You must be signed in to change notification settings

Richard2926/arduinoGestureRecognition

Repository files navigation

arduinoGestureRecognition

Introuducing The-Ben-3 recognition device.

Using Logistic Regression to train data from an accelerometer in order to recognize and categorize gestures.

Key features: Using simple components like a microcontroller and deploying complex machine learning algorithms to obtain clean results.

All the major components of code are soft coded and hence, you can use them to your advantage, the only "code" you will have to modify, is labeling your data in reshapeDataNormalize.

The objective is using an advanced optimization method in order to minimize the cost function of the logistic Regression algorithm. Then compute Accuracy.

There is an inbuilt function that I have created in order to check for broken data samples, so you dont have to go looking through thousands of lines of code.

testStuff is just a file for you to, well, test any code you are unfamiliar with.

Currently, I am trying to gain decent results by using neural networks, I am having trouble debugging the code, hopefully it will be complete in a few days time.

Then, I will also see the outcome of Support Vector Machines

All changes will be updated.

About

Using Logistic Regression to train data from an accelerometer in order to recognize and categorize gestures. Key features: Using simple components like a microcontroller and deploying complex machine learning algorithms to obtain clean results.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published