Answers.Body: <p>I find it useful to refer to scikit-learn's <a href="https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html" rel="nofollow noreferrer">Choosing the right estimator</a> cheatsheet, using it of course with a bit of consideration and thought.</p>
  <p>In your case we are talking about a <strong>supervised regression</strong> problem in which you have to predict a numeric value from three other values. The first thing to note is that, having only three input features, you should probably first <strong>plot</strong> the data and try exploring it with your own eyes. You may find out that one or more of those features have a clear relationship with the target variable, for example a linear correlation.
  In that case, you could try fitting a <a href="https://scikit-learn.org/stable/modules/linear_model.html" rel="nofollow noreferrer">linear model</a> to your data.</p>
  <p>One important aspect that you don't mention is the <strong>number of data points</strong> you have available. Having enough data for both training and testing is essential, although the exact number depends on how complex the relationship between variables is. Good luck.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-08-19T11:33:01.650Z
Answers.LastActivityDate: 2022-08-19T11:33:01.650Z
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Body: <p>I need to select the most suitable ML algorithm for an academic project. I have a dataset earn from lab which includes the long of an element and 3 factors that we believe impact the long of the mentioned element. I want to predict the length of the element by using those 3 factors.
  Probably I should use supervised algos but which one?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2022-08-19T12:57:09.513Z
Comments.Text: Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.
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Tags: <machine-learning><algorithm>
Title: Choose the right algorithm
UserDisplayName: Samaneh salehi nasab
ThreadText: # Choose the right algorithm
  
  (Asked by: username_0 on 2022-08-19)
  
  I need to select the most suitable ML algorithm for an academic project. I have a dataset earn from lab which includes the long of an element and 3 factors that we believe impact the long of the mentioned element. I want to predict the length of the element by using those 3 factors.
  Probably I should use supervised algos but which one?
  
  **Tags:** machine-learning, algorithm
  > **Comments:**
  > **username_1**: Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2022-08-19. Score: 1
  
  I find it useful to refer to scikit-learn's [Choosing the right estimator](https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html) cheatsheet, using it of course with a bit of consideration and thought.
  
  In your case we are talking about a **supervised regression** problem in which you have to predict a numeric value from three other values. The first thing to note is that, having only three input features, you should probably first **plot** the data and try exploring it with your own eyes. You may find out that one or more of those features have a clear relationship with the target variable, for example a linear correlation.
  In that case, you could try fitting a [linear model](https://scikit-learn.org/stable/modules/linear_model.html) to your data.
  
  One important aspect that you don't mention is the **number of data points** you have available. Having enough data for both training and testing is essential, although the exact number depends on how complex the relationship between variables is. Good luck.
  
  
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