This ML experiment is aimed at identifying and capturing the gestures made by the users using the x,y and z coordinates.
**List of Attributes:** **Class** - Integer. Ranges from 1 to 5 with 1=Fist(with thumb out) 2=Stop(hand flat) 3=Point1(point with pointer finger) 4=Point2(point with pointer and middle fingers) 5=Grab(fingers curled as if to grab). **User** - Integer. User ID. Can be used as an identifier **Xi** - Real. The x-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 5. **Yi** - Real. The y-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 5. **Zi** - Real. The z-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 5. Based on the values of Xi, Yi and Zi, The class is predicted. The ML algorithm used here is Multiclass Decision Forest under Classification (as it is efficient in computation and memory usage during training and prediction). The model is also evaluated.