When building a simple perceptron neural network we usuall passes a 2D matrix of input of format (batch_size,features) to a 2D weight matrix, similar to this simple neural network in numpy. I alway...

I've always heard that the XOR problem can not be solved by a single layer perceptron (not using a hidden layer) since it is not linearly separable. I understand that there is no linear function th...

I have implemented the Perceptron Learning Algorithm in Python as below. Even with 500,000 iterations, it still won't converge. I have a training data matrix X with target vector Y, and a weight ...

I am beginner in neural networks. I am learning about perceptrons. My question is Why is weight vector perpendicular to decision boundary(Hyperplane)? I referred many books but all are mentioning t...

I have a training data for NN along with expected outputs. Each input is 10 dimensional vector and has 1 expected output.I have normalised the training data using Gaussian but I don't know how to n...

Given the simple OR gate problem: or_input = np.array([[0,0], [0,1], [1,0], [1,1]]) or_output = np.array([[0,1,1,1]]).T If we train a simple single-layered perceptron (without backpropagation), ...

If we have 10 eigenvectors then we can have 10 neural nodes in input layer.If we have 5 output classes then we can have 5 nodes in output layer.But what is the criteria for choosing number of...

This question is totally re-written after I confirmed my results (the Python Notebook can be found here) with a piece of code written by someone else (can be found here). Here is that code instrume...

I am taking this course on Neural networks in Coursera by Geoffrey Hinton (not current). I have a very basic doubt on weight spaces. https://d396qusza40orc.cloudfront.net/neuralnets/lecture_...

I am having trouble understanding the weight update rule for perceptrons: w(t + 1) = w(t) + y(t)x(t). Assume we have a linearly separable data set. w is a set of weights [w0, w1, w2, ...] where...

The Situation: I am wondering how to use TensorFlow optimally when my training data is imbalanced in label distribution between 2 labels. For instance, suppose the MNIST tutorial is simplified to ...

I understand the following: In 2D space, each data point has 2 features: x and y. The weight vector in 2D space contains 3 values [bias, w0, w1] which can be rewritten as [w0,w1,w2]. Each d...

I'm currently experimenting with scikit-learn's neural net capabilites. Is there are way to set the number of output nodes in its MLPClassifier? I know you can set the number of hidden layers by pa...

I'm trying to make a basic MLP example in keras. My input data has the shape train_data.shape = (2000,75,75) and my testing data has the shape test_data.shape = (500,75,75). 2000 and 500 are the nu...

Could someone please give me a mathematical correct explanation why a Multilayer Perceptron can solve the XOR problem? My interpretation of the perceptron is as follows: A perceptron with two inp...

I have programmed a multilayer perception for binary classification. As I understand it, one hidden layer can be represented using just lines as decision boundaries (one line per hidden neuron). Th...

Hi I'm pretty new to Python and to NLP. I need to implement a perceptron classifier. I searched through some websites but didn't find enough information. For now I have a number of documents which ...

Isn't it true that if a bias is not present, a line passing through origin should be able to linearly separate the two data sets?? But the most popular answer in this -->> question says y ^ | -...

I have to do a project that tries to scan the shape of the vehicles and detect what type of vehicle it is , the scanning will performed with a sensors called “vehicle scanner” they are just 50 beam...

I'm having sort of an issue trying to figure out how to tune the parameters for my perceptron algorithm so that it performs relatively well on unseen data. I've implemented a verified working per...

How I might plot the decision boundary which is the weight vector of the form [w1,w2], which basically separates the two classes lets say C1 and C2, using matplotlib? Is it as simple as plotting a ...

with single-layer perceptron it's easy to find the equation of the "separating line" (I don't know the professional term), the line that separate between 2 types of points, based on the perceptron'...

I'm trying to perform leave-one-out cross validation for modelling a particular problem using Back Propagation Neural Network. I have 8 features in my training data and 20 instances. I'm trying to ...

I'm having trouble seeing what the threshold actually does in a single-layer perceptron. The data is usually separated no matter what the value of the threshold is. It seems a lower threshold divid...

So here is shown a simple example - 2 floats as data + 1 float as output: Layer 1: 2 neurons (2 inputs) Layer 2: 3 neurons (hidden layer) Layer 3: 3 neurons (hidden layer) Layer 4: 1 neurons (...