sign-language-prediction

Machine learning models used to predict signs for the deaf.

The project data(signs) has been collected using Microsoft Xbox Kinect.
The data was then saved to an Microsoft Excel file.

Using machine learning to predict signs.

The data was divided into 75-25 ratio for train and test data. Then the following machine learning algorithms were used to build models:

Support Vector Machine(SVM)
k-Nearest Neighbor(kNN)
Random Forest(RF) Then all of them were used to predict values on the test set.

Then I combined all these predictors and ensembled them to improve accuracy. The overall accuracy of the model was improved.

I plotted the accuracy tables where you can see accuracy of each algorithm for each possible outcome label. I also have plotted graphs for this table for better visualization as to which algorithms predicts better. And then I finally plotted graph for the ensembled model as well.