I have a dataset that is in the form of categorical timeseries: (specifically, we either know or don't know the values of 6 degrees of freedom of an object at any given time). If we know it, it's marked as 1; otherwise, it's marked as 0. I would like to know if there is any machine learning algorithm or concept that can be used for this dataset in order to predict the presence or absence of any of the six degrees of freedom in some time in future. I do have little of background in data science, but I have never dealt with such a dataset before. I would appreciate anyone giving me some advice on how to proceed.

One important note: Every row has its own unique state [x, y, z, v_x, v_y, v_z] meaning that the object can NOT possibly be at the same motion state even twice!

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