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Train a neural networks with this format of data?

Michel Mesedahl
Posted 7 years ago

Is is possible to train this format of data? 

{{21, 30, 39, 45, 46, 44}->{1, 5, 20, 28, 52, 24}
{31, 52, 36, 34, 26, 32}->{9, 47, 40, 34, 7, 11}
{48, 35, 44, 8, 45, 4}->{25, 30, 4, 28, 21, 35}
.
.
.
{15, 42, 49, 17, 44, 30}->{22, 11, 19, 23, 15, 18}}

Will a Neural Network learn these associations?

Thank You Michel
POSTED BY: Michel Mesedahl
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How would I deal with a Data file of this type that is 66 GB?

Michel
POSTED BY: Michel Mesedahl
POSTED BY: Sjoerd Smit

We have some excellent videos and tutorials on Machine Learning!

Here are some of the resources you can use:

(there are many many more ... just search online for 'wolfram machine learning')
POSTED BY: Arnoud Buzing

Thank You I need to do more in-depth reading on layers.

Have an Excellent day
POSTED BY: Michel Mesedahl

Thank You Would training be learned on whole Vector representation to whole Vector representation
Or component to component .

Michel
POSTED BY: Michel Mesedahl

If you use only regular LinearLayers (often called "dense" layers) and elementwise layers (like Ramp) such as I did in my example, the learned representation will be vector-to-vector. A linear layer is nothing more than a matrix multiplication with trainable matrix elements.
POSTED BY: Sjoerd Smit

There's no reason why a neural network wouldn't be able to learn a vector-to-vector mapping. Here's an example:

data = {
 {21, 30, 39, 45, 46, 44} -> {1, 5, 20, 28, 52, 24},
 {31, 52,  36, 34, 26, 32} -> {9, 47, 40, 34, 7, 11},
 {48, 35, 44, 8, 45,  4} -> {25, 30, 4, 28, 21, 35},
 {15, 42, 49, 17, 44, 30} -> {22, 11, 19, 23, 15, 18}
};

trainedNet = NetTrain[
  NetChain[{
    LinearLayer[10],
    Ramp,
    LinearLayer[]
    }
   ],
  data,
  TimeGoal -> 30
]

Note that by specifying the final layer as LinearLayer[], the network will figure out automatically from the data what shape the output should be (in this case, a length-6 vector).
POSTED BY: Sjoerd Smit
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