Comments (6)
Hi, I'm not sure if I understand correctly what you try to do, but it seems this is a quite standard regression problem where what you call inputs is the training set and what you call outputs is a test set. Your actual inputs in training are surf_x, surf_y, and surf_z, and fitted is the target. Then, in testing, in your "outputs" dataset, you only have surf_x, surf_y, and surf_z and want to find the "fitted" values. So what you need is something like the following to train the model:
rbf_res <- RSNNS::rbf(x = inputs[,c("surf_x","surf_y","surf_z")],
y = inputs[,"fitted"])
Then, to predict on your new data, you need:
res = predict(rbf_res, newdata=outputs)
Any particular reason to use RBF for this? Otherwise I'd use any standard Machine Learning algorithm like a random forest or so.
from rsnns.
Cubic RBF interpolation has been specifically validated for my goal: https://ieeexplore.ieee.org/document/5626616
I'm about to leave on an extended vacation and will test this when I return, thank you!
from rsnns.
Sure, give it a go and let me know if it works (or not).
from rsnns.
Can this be used to fit a cubic or multiquadric RBF?
from rsnns.
It seems to have Multiquadratic, yes. Best you check in the SNNS Manual, page 175ff for the details: http://gentoo.osuosl.org/distfiles/SNNSv4.2.Manual.pdf
from rsnns.
There are some demos in RSNNS that should allow you to figure out how to use these parameters from SNNS in RSNNS. They are in the demo folder in the package.
from rsnns.
Related Issues (19)
- RBF sites/links handling HOT 1
- How to implement a time-delay neural network using RSNNS? HOT 5
- Loading *.pat files HOT 1
- Where is old `loadNet()` HOT 1
- How to assign new learning algorithm ? HOT 1
- Unable To access repository for package installation in R HOT 1
- Activation Functions about RELU HOT 5
- Different results using Windows or Linux HOT 1
- Jordan segfault when used with more than one layer
- plotting function HOT 2
- Doubt about the forecast with RSNNS
- How to show the values of hidden nodes in a mlp model HOT 3
- predict method for pruned networks HOT 5
- A question for installing RSNNS HOT 4
- R crashes upon running mlp() HOT 3
- How do bias work at a mlp network? HOT 4
- Explanation for a command HOT 2
- Suggestion of init method HOT 9
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from rsnns.