Determining weight matrix [closed] - neural-network

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I need to design a neural network which has the following behavior:
p(1)={0,1,1,1} outputs a(1)={0,1,0,0}
p(2)={1,1,0,1} outputs a(2)={0,0,1,0}
p(3)={0,0,1,0} outputs a(3)={0,0,0,1}
p(4)={0,0,1,1} outputs a(4)={1,1,0,1}
How can i do so? Which type of neural network should I use? Which learning method can be used here?
Thanks.

At first glance it seems as though you could use a simple feedforward neural network with one input layer one, one hidden layer and one output layer. You can use your training data to train the neural network using the backpropogation algorithm.
See this page for more details:
http://en.wikipedia.org/wiki/Backpropagation

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How to improve perfomance of CNN and reduce overfitting? [closed]

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I am working on a small computer vision project and I'm using convolutional nets for classification. I have already used dropout, l1, l2 regularization and data augmentation to reduce overfitting. Are there any other techniques and algorithms for improving model accuracy and reducing overfitting?
there could be a 100 solutions
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Clustering with Autoencoder [closed]

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I made a model for clustering and it's encoded dimension is about 3000. To check if the autoencoder is well established, I draw a 2d_pca plot and 3d_pca and the plots look nice.
My question is that, what is general way to cluster with this encoded features?
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Third: to use some encoded pca features explaining almost 70% variance.
I think usual papers don't refer to it.

How to compare different models configurations [closed]

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I am implementing a neural network model for text classification. I am trying different configurations on RNN and lstm neural network.
My question: How to compare these configuration, should I compare the models using the training set accuracy, validation accuracy or testing set accuracy?
I will explain how I finally compared my different RNN models.
First of all, I used my CPU for model training. This will ensure that I get the same model parameters each run as GPU computations are known to be non-deterministic.
Secondly, I used the same tf seed for each run. To make sure that the random variables generated in each run is the same.
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can Clustering be used for predictive Analytics? [closed]

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Im still not sure how clustering can be used for predictive analytics?
can someone tell me how to predict the future from extracting clusters?
generally, clustering isn't used for prediction but for labeling or analyzing existing set of data points.
after you use clusters to label your data points and divide them into groups based on common traits, you can run other prediction algorithms on that labeled data to get predictions.
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How to create block diagram and analysis a simple RLC circuit in MATLAB? [closed]

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i have this! RLC simple circuit
i want to analysis this circuit with different values of Resistance
but i dont know how can i draw a block diagram and simulink it with matlab, i just searched internet and found some libraries,but i didn't find anything special for my work, please if you have experience in this analysis help me and let me know how can i analysis it with MATLAB simulink
i think its very simple circuit , and if i found a way to create this in MATLAB , Matlab can analysis that easily, and i want to analysis this for different values of resistance , and i have constant L and C , for inductor and capacitor
If you're allowed and have access to it, the easiest way would be to use Simscape, which has an electrical library. See Simulink Simscape simple circuit not working for a similar question.