Answers.Body: <p>Not familiar with RBF but when you have a small data set image augmentation can help. You can do this easily with the Keras ImageDataGenerator, documentation is <a href="https://keras.io/preprocessing/image/" rel="nofollow noreferrer">here</a>. Alternatively you can create image augmentation yourself using image processing models like PIL or CV2.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-04-27T07:44:57.380Z
Answers.LastActivityDate: 2020-04-27T07:44:57.380Z
Answers.UserDisplayName: Gerry P
Body: <p>I'm a computer engineering student and I'm about to work on my master thesis. My professor gave me a small dataset with brain Computed Axial Tomography records. I would like to use deep learning to help doctors diagnose a certain disease (obviously, I've also got the data for doing supervised learning). </p>
  
  <p>Since the dataset is small, is <a href="https://en.wikipedia.org/wiki/Radial_basis_function_network" rel="nofollow noreferrer">radial basis function network</a> a good solution? What do you think?</p>
  
  <p>Btw, if you have any type of tips in using the RBF network for this kind of project I would be really grateful.</p>
  
Tags: <neural-networks><machine-learning><deep-learning><supervised-learning>
Title: Is radial basis function network appropriate for small datasets?
UserDisplayName: AleWolf
ThreadText: # Is radial basis function network appropriate for small datasets?
  
  (Asked by: username_0 on 2020-04-24)
  
  I'm a computer engineering student and I'm about to work on my master thesis. My professor gave me a small dataset with brain Computed Axial Tomography records. I would like to use deep learning to help doctors diagnose a certain disease (obviously, I've also got the data for doing supervised learning).
  
  Since the dataset is small, is [radial basis function network](https://en.wikipedia.org/wiki/Radial_basis_function_network) a good solution? What do you think?
  
  Btw, if you have any type of tips in using the RBF network for this kind of project I would be really grateful.
  
  **Tags:** neural-networks, machine-learning, deep-learning, supervised-learning
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-04-27. Score: 1 | Accepted answer
  
  Not familiar with RBF but when you have a small data set image augmentation can help. You can do this easily with the Keras ImageDataGenerator, documentation is [here](https://keras.io/preprocessing/image/). Alternatively you can create image augmentation yourself using image processing models like PIL or CV2.
  
  
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