Questions tagged [rbf-network]

A radial basis function (RBF) network is a neural network that uses a radial basis function as an activation function.

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Interpolation with radial basis functions (RBF) is failing for some reason

This is not a pure programming question. I am trying to understand what's going on when I try to use RBF with 5 centers. I am using R to exemplify, see below. My data set: ...
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Why aren't neural networks used with RBF activation functions (or other non-monotonic ones)?

In most work I've seen, MLPs (multilayer perceptron, the most typical feedforward neural network) and RBF (radial basis function) networks are compared as distinct models, where MLP neuron outputs $\...
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How are radial basis functions (RBFs) networks extended to use multiple layers?

I am trying to understand the interpretation of radial basis functions (RBFs) as networks and then trying to understand the relationship it has to "normal" neural networks and how to extend them to ...
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Implementing a Radial Basis Function Network. Question about missing information

I would like to implement a Radial Basis Function (Neural) Network. Specifically, I would like to implement the network as described in this paper: http://www.ncbi.nlm.nih.gov/pubmed/15732389. The ...
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What is the role of length scale bound in sklearn Radial Basis Function

The radial basis function provided by SkLearn (reference) has two parameters: length scale and length scale bounds. I understand that the length scale controls the importance of the coordinates of the ...
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Is SVM RBF applied to both classes?

Lets say i have following 1D data (position on x), color is target class and I need a classifier which classifies green from red: I decided to use SVM. Data is clearly not linearly separable, so i ...
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Gaussian RBF vs KNN explanation

I was studying SVM ML alghorythm and I was wondering about solution for non-linear cases. As I understand it for know, SVM tries to find hyperplane or object in defined n-dimensional space, which ...
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Adding new center in an RBF network without memorizing previous training examples

Suppose we train an RBF by minimizing the LSE on a couple of training points and we are doing it incrementally in an online fashion. So basically we update the QR factorization using e.g. Givens ...
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Why SVM with RBF kernel always classify to one group?

I've downloaded Dog vs Cat from kaggle dataset and utilize OpenCv 3.2 Machine Learning library and c++ language, And I choose 60-40(percent for train/test) from training set(kaggle test set do not ...
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Connection between Gaussian Process Regression and regression with Gaussian basis functions

The other day a coworker was claiming that Gaussian Process Regression with a squared exponential kernel (from now on, GPR) for a data set $D=\{\mathbf{x}_i,y_i\}_{i=1}^N$ could be interpreted as just ...
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Better classification performance when using an RBF kernel function in high dimensional space?

I'm learning about SVM's and understand that boosting something into a higher dimension can sometimes help separate the data better. However, if I were to perform 1 nearest neighbor with the RBF ...
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553 views

Tuning hyperparameters of Radial Basis Function Network for regression

I started using Radial Basis Function Networks for regression (see here for an overview of RBFNs). The specifics are: $10^3 < n < 10^4$ input points, $x^{(i)} \in \mathbb{R}^d$, where $d$ is ...
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RBF Network for classification

I would like to know how it is calculated the outcomes (i.e. the output layer output) of a RBF Network for a classification problem. My code fits the hidden->output weights with linear regression ...
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RBF versus standard classical analysis for empirical power functions

Sorry if the previous post caused any inconvenience to you. I am a newbie in Radial Basis Functions (RBF) and this is the first time I post a question. I have 80 pairs of Y=body weight and X= body ...
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Why using RBF helps?

Let's say we are doing logistic regression for classification. When the features are used directly, it means we are using some characteristics (features) of the object to classify them. But when using ...