Train a Neural Network with multidimensional matrices

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Francesco Basciani
Francesco Basciani 2020-2-24
回答： Srivardhan Gadila 2020-3-4
I want use neural network to perform binary prediction for a set of 10 robotic manipulators that have to converge to a target position when arranged in a crowded environment. Each robot is characterized by 5 feature and my dataset is composed of 2000 simulations.Then if I indicate with N the number of features of the robots, with M the number of simulations and with R the number of the robots, I have a N x M x R matrix. The problem is that i cannot feed a Neural network with the data in this form and I am looking for another way to arrange the data for the Network. It is important that when i have to split the data for training, validation and test, the split is performed on the number of simulation M, and not on the number of robots R.
Thank you

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回答（1 个）

Srivardhan Gadila
If you are thinking of a fullyconnected network then use the imageInputLayer for giving the input to the network and use the dividerand for splitting the dataset across M. Reshape your N x M x R matrix to N x R x 1 x M or R x N x 1 x M matrix using reshape function
Also refer to List of Deep Learning Layers.

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