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No gyro, not enough information.



I also tried my code without the gyro, and incredibly, the accuracy is still pretty high (86.90% rather than 90.77%).


Have you tried your classifier with a different accelerometer dataset? That will be a good test of generalization.


I am co-writing a paper with a Ph.D. student and he is currently working on trying with other datasets. We are also trying different architectures, combining multiple LSTMs (stacked, residual connections + batch normalization, bidirectional LSTMs, and on)




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