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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Increasing training set decreases accuracy
I've ~16000 labeled data. I split it in ~8000 for training and ~8000 for testing of my RBF neural network, find the best hyperparameters (RMSE from 1.2 to 1.4*) and finally train the model on the ...
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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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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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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 ...
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How do the mapping function phi(x) of a RBF kernel?
I'm trying to implement a paper that used SVM and an improve of it with Bayesian decision theory. How do I do the mapping feature $\phi(x)$ that appears in the decision function?
The paper used an ...
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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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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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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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What is the difference between MLP and RBF?
What are the main differences between two types of feedforward networks such as multilayer perceptrons (MLP) and radial basis function (RBF)?
What are the fundamental differences between these two ...
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RBF network normalization, standardization in MATLAB
First of all, is it good to do normalization and standardization for Radial basis neural network?
Does MATLAB do that automatically for RBF? I've read that MATLAB does normalization and ...
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Delimitation: feed forward- and radial basis networks
I am trying to get myself involved with the topic of neural networks for the purpose of a GPGPU project at university. Now, Wikipedia distinguishes between "Feed forward neural networks" and "Radial ...
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RBF: Linear and non linear cases
I had a course in machine learning but I still have some questions about the RBF (Radial Basis Functions):
What is the difference between RBF in linear and non linear cases?
How does the RBF work in ...
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When to use RBF networks instead of multilayer perceptron?
I understand that a radial basis function neural network (RBF) usually has 1 hidden layer, and it differs from a multi-layer perceptron (MLP) via its activation and combination functions among other ...
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Is this the right way to apply grid search and 5 fold validation with sklearn?
I am using support vector machines and the rbf kernel to learn.
I would like to split my training data where 80% is the training set and 20% is the validation set.
Then I would like to apply a grid ...
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Does a radial basis function network work in high dimensions?
It seems that a single-layer radial basis function network with normalized weights is the same thing as kernel smoothing (see e.g. Haykin Neural Networks: a Comprehensive Foundation, Section 5.12).
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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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Why don't people use deeper RBFs or RBF in combination with MLP?
So when looking at Radial Basis Function Neural Networks, I've noticed that people only ever recommend the usage of 1 hidden layer, whereas with multilayer perceptron neural networks more layers is ...
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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 are the best R packages for a classification problem with use of Neural networks [closed]
Surfing on the internet shows me that there are a lot of different packages and functions which can be used to train neural networks via R.
packages such as 'RSNNS', 'nnet','neuralnet', etc.
I'm ...
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Recommended/estimated number of radial basis functions in RBFN
I am attempting to make a Radial Basis Function Network to see if a relationship exists between input/output data that I have been collecting. I have hit a bit of a brick wall with a few issues, and ...
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Radial basis function network - G function?
I'm trying to understand Radial Basis Function Network.
I have (don' know how to write proper formatter mathematical functions here..):
$x = [ -1.0000, -0.5000, 0,0.5000,1.0000]$
$y_i = f(x_i)$
$f(...
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