Radial Basis Functions (RBFs) are a class of functions used to determine some metric of relation between an arbitrary point and a center point.
Questions tagged [rbf]
10 questions
6
votes
3 answers
Why spectral clustering results in disjointed cluster?
I'm working on a project where I have to dynamically cluster the position of objects with respect to one coordinate. So I'm essentially dealing with subsequent frames and each frame represents a one-dimensional dataset. The intuition behind…
Kuba_
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1 answer
Notation unclear - Radial Basis Funtion
In Chapter 6 (Deep Forward Networks) on Page 193 of Deep Learning they talk about the design of Hidden Units.
The Radial Basis Function is introduced as follows:
$$
h_i = exp\big{(}-\frac{1}{\sigma_i^2}||W_{:,i} − x||^2\big{)}
$$
What does the colon…
Linsane
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Computation of kernel matrix using radial basis kernel in svm
I want to compute a kernel matrix using RBF on my own. The training data is multidimensional. My query is whether we will apply
$$e^{-\gamma(x-y)^2}$$
for each dimension and then sum the values across all dimension?
Akanksha Pathak
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1 answer
RBF kernel can classify two classes as in figure?
As you can see, I have some points (belonging to red and blue class), and I would to use an RBF kernel but I think that an RBF kernel can make points linearly separable only if they are located in perfect circular way. In this case I don't know how…
Ric
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2
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1 answer
RBF neural network python library/implementation
I want to use a Radial Basis Function Neural Network for my thesis.
Is there any library that implements it? And in the negative case, which is the best library to implement it?
phemps
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vote
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Unable to train neural network for prediction
My data consists of a time series of values $\pm1$ and I am trying to apply a RBF NN as a function approximator. Essentially, the NN will take as input one data sample and predict the next sample (one step ahead prediction). However, my network is…
Sm1
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How to use a RBF kernel to create a "Kernel Space" using the similarity of each pair of point?
I am trying to use Semi-Unsupervised clustering using reinforcement learning following this paper.
Assume I have n data-points each of which has d dimensions. I also have c pairwise constraints of whether two elements are supposed to be in the same…
raff7
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Can we optimize heterogeneous parameters of RBF Network using Gradient Descent?
There're three parameters in the Radial Basis Function Networks (RBFN).
Centers of RBFs
Width of RBFs
Weights of RBFs
It's a fact that Weights can be easily updated using a simple Gradient Descent. My question is: Can we optimize Centers and…
Tarlan Ahad
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How to implement an RBF network in Pytorch?
This is how I understand an RBF network.
From a set of points $P:=\{p_i\}_{i \in I}$ and values $F:=\{f_i\}_{i \in I}$, an RBF network is an approximation $\tilde{f}(x)$,
$$\tilde{f}(x) = \sum_{j \in C} w_j \phi(x - c_j)$$
The $\{w_j\}_{j \in C}$…
tmaric
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Why radial basis networks are not suffer from getting stuck in the local minima
I have read some articles about RBF networks. I am not able to understand how the training of RBF networks help to overcome stuck in local minima. Please explain how it works.
sfitzjc919
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