<p>My Problem consists of Input sequences in the form of <span class="math-container">$x=[B,z]$</span> and one output <span class="math-container">$y_i$</span> for each data point <span class="math-container">$x_i=[B,z_i]$</span>. For one sequence/dataset <span class="math-container">$B$</span> is a constant, whereas <span class="math-container">$z$</span> is continously between 0 and 5.</p>
<p>In the moment I just train a standard MLP on this. However, I wonder if I can &quot;help&quot; my neural network because I know, that <span class="math-container">$y_i$</span> is a smooth function of <span class="math-container">$z_i$</span>. This seems analog to a time series problem, where I computate my solution at <span class="math-container">$y_i(t=0)$</span> and use this information for the prediction of <span class="math-container">$y_i(t=1)$</span>.</p>
<p>Am I right with this assumption? Can I use RNN or a combination of RNN with MLP for this?</p>

CC BY-SA 4.0
2022-03-14T09:08:57.797Z
Can you please edit your post to format the symbols and equations with mathjax to improve the readability? Moreover, the question in the title is very general. Please, put your **specific question** in the title.
nbro
CC BY-SA 4.0
2022-03-14T14:35:20.497Z
Done and changed title
Gesetzt
CC BY-SA 4.0
2022-03-15T15:17:24.980Z
I think the best way is just to try it out. If it is in fact something like a time series RNN/LSTM can be helpful because in many applications (but not all) they yield good results when having sequence data.
PeterBe
<neural-networks><recurrent-neural-networks><time-series>
MLP or RNN for Regression of Smooth Function (No Time Data)?
Gesetzt
# MLP or RNN for Regression of Smooth Function (No Time Data)?

(Asked by: username_0 on 2022-03-13)

My Problem consists of Input sequences in the form of $x=[B,z]$ and one output $y\_i$ for each data point $x\_i=[B,z\_i]$. For one sequence/dataset $B$ is a constant, whereas $z$ is continously between 0 and 5.

In the moment I just train a standard MLP on this. However, I wonder if I can "help" my neural network because I know, that $y\_i$ is a smooth function of $z\_i$. This seems analog to a time series problem, where I computate my solution at $y\_i(t=0)$ and use this information for the prediction of $y\_i(t=1)$.

Am I right with this assumption? Can I use RNN or a combination of RNN with MLP for this?

**Tags:** neural-networks, recurrent-neural-networks, time-series

> **Comments:**
> **username_1**: Can you please edit your post to format the symbols and equations with mathjax to improve the readability? Moreover, the question in the title is very general. Please, put your **specific question** in the title.  
> **username_0**: Done and changed title  
> **username_2**: I think the best way is just to try it out. If it is in fact something like a time series RNN/LSTM can be helpful because in many applications (but not all) they yield good results when having sequence data.  

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## 0 answers

