Deep learning for non sequential data regression

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Anas Rao
Anas Rao 2022 年 8 月 4 日
回答済み: Meet 2024 年 9 月 25 日
Does deep learning is applicable for non sequential data for regression and if yes which models are preffereably applied for training purpose and any useful material/tutorial for learning prespective?

回答 (1 件)

Meet
Meet 2024 年 9 月 25 日
Hi Anas,
Yes, deep learning can be applied to non-sequential data for regression tasks. MATLAB's Deep Learning Toolbox offers a variety of models and functions that can be effectively utilized for this purpose.
Here are some models you can consider for regression tasks:
  • Feedforward Neural Network: These are fundamental neural networks where connections between nodes do not form loops. They are particularly well-suited for handling regression tasks with non-sequential data.
  • Convolutional Neural Network: Although typically used for image data, these networks can also be adapted for regression tasks.
You can refer to the resources below for more information:
  1. https://www.mathworks.com/help/releases/R2019b/deeplearning/ref/feedforwardnet.html
  2. https://www.mathworks.com/help/releases/R2019b/deeplearning/ug/introduction-to-convolutional-neural-networks.html
  3. https://www.mathworks.com/help/releases/R2019b/deeplearning/examples/train-a-convolutional-neural-network-for-regression.html
Hope this helps!!

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