Your question is a bit broad, but i’ll try to answer nonetheless. To imitate a subjects behavior you could use and LSTM network which has an understanding of the state it’s in (in your case the state may include information about how fast and in which direction the dot is going and where the pointer … Read more
As sascha observes, constant initial weights aren’t a solution in general anyway because you have to break symmetry. Better solution for the particular context in which I came across the problem: a random number generator that gives the same sequence regardless of type. dtype = np.float64 # Random number generator that returns the correct type … Read more
Answers to your questions: 1 – This is a binary perceptron algorithm, working on an offline batch. 2 – as you wrote – Y is the labels vector. each label can be either be 1 or -1. 3 – The rational of testing if y*a<=0 is to check if the perceptron classified a certain sample … Read more
If you look at the feedforwardnet MATLAB help page there is this example: [x,t] = simplefit_dataset; net = feedforwardnet(10); net = train(net,x,t); view(net) y = net(x); perf = perform(net,y,t) This is almost what you want. The feedforwardnet can take an array of different hidden layer sizes, so we can do: net = feedforwardnet([2 10 2]); … Read more
Is there any standard rule for considering the best result or at which stage I have to stop train the data with minimum error solved Is there any standard rule for considering the best result or at which stage I have to stop train the data with minimum error
I didn’t check your code but… No, you can’t use fixed weight like that. Each node in your hidden layer will get larger and larger values as you increase the amount of inputs. Sigmoid will scale the large values to 1. Think about it: Let’s say that you have 100 inputs each having “random” input … Read more
An inability to overfit may be caused by a lack of network capacity or a bug in your code itself. Are you training the model from scratch? Did you write the model yourself? Are you working on a task at a similar scale to Imagenet classification? Plateauing of a loss is to be expecting during … Read more
“Annealing”, in this sense, is an analogy to a chemical process in which temperature is reduced. Here, too, the ‘temperature’ term in the softmax is reduced, changing it gradually from a ‘soft’ sigmoid function to a ‘sharp’ argmax Try plotting a softmax function for yourself with different temperatures, you’ll see the difference… solved Terms in … Read more
TLDR; Reinforcement learning In general, training agents uses reinforcement learning. It is different than what you explained, because it seems as if you want to define a fitness heuristic to tell the agent whether it is doing OK or not, which might be biased. Reinforcement learning also has biases, but they are researchedand studied. A … Read more
Outputs of a neural network are not probabilities (generally), so that could be a reason that you’re not getting the “1 – P” result you’re looking for. Now, if it’s simple logistic regression, you’d get probabilities as output, but I’m assuming what you said is true and you’re using a super-simple neural network. Also, what … Read more
maybe is the best to load all .mat files which contain parameters you want to use for training of neural network and put all your input parameters into one variable, and than to use that variable as the input for neural network. solved Training neural network in matlab
Introduction This article provides an overview of how to train a neural network in MATLAB. It covers the basics of neural networks, the different types of neural networks, and the steps involved in training a neural network. It also provides some tips and tricks for optimizing the training process. Finally, it provides some examples of … Read more
Here’s a list of what I see wrong: deep breath The indexing syntax (:1) is incorrect. Perhaps you mean (:,1) as in “all rows of column 1”. There is no such thing as a do…while loop in MATLAB. Only FOR and WHILE loops. Also, your for loop is defined wrong. MATLAB has a different syntax … Read more