Answers.Body: <p>There are a ton of sample datasets our there you can play with. A bunch of good ones install with R in the datasets package.  Luckily you can download them independently if you're not an R user.  Try  <a href="https://vincentarelbundock.github.io/Rdatasets/datasets.html" rel="nofollow">https://vincentarelbundock.github.io/Rdatasets/datasets.html</a></p>
  
  <p>You might also be interested in the <a href="http://yann.lecun.com/exdb/mnist/" rel="nofollow">MNIST database</a> which is one of the canonical databases used in handwriting recognition research.</p>
  
  <p>Beyond that, you can look at / ask on <a href="http://datasets.reddit.com" rel="nofollow">http://datasets.reddit.com</a> and/or <a href="http://opendata.reddit.com" rel="nofollow">http://opendata.reddit.com</a> and you'll find all sorts of useful datasets.</p>
  
  <p>And finally, don't overlook the <a href="http://archive.ics.uci.edu/ml/" rel="nofollow">UCI Machine Learning Repository</a>.</p>
  
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Answers.UserDisplayName: mindcrime
Answers.Body: <p>A popular dataset is the fisher iris dataset. It consists of 150 samples each with a dimensionality of 4. You can find it at
  <a href="http://archive.ics.uci.edu/ml/datasets/Iris" rel="nofollow">http://archive.ics.uci.edu/ml/datasets/Iris</a></p>
  
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Answers.LastEditDate: 2016-10-13T11:00:03.283Z
Answers.UserDisplayName: hh32
Answers.Body: <p>If you want to solve a <a href="https://en.wikipedia.org/wiki/Multiclass_classification" rel="nofollow noreferrer">multi-class classification</a> problem, you could use the famous <a href="https://en.wikipedia.org/wiki/Iris_flower_data_set" rel="nofollow noreferrer">iris flower dataset</a>, which was <a href="https://archive.ics.uci.edu/ml/datasets/iris" rel="nofollow noreferrer">introduced by Fisher in 1936</a>. In this dataset, each flower has (only) <span class="math-container">$4$</span> features (the inputs), namely</p>
  
  <ul>
  <li>petal length, </li>
  <li>petal width, </li>
  <li>sepal length, and </li>
  <li>sepal width</li>
  </ul>
  
  <p>There are <span class="math-container">$3$</span> classes (the outputs)</p>
  
  <ul>
  <li>iris setosa, </li>
  <li>iris virginica, and </li>
  <li>iris versicolor</li>
  </ul>
  
  <p>And there are a total of <span class="math-container">$150$</span> observations (or records).</p>
  
  <p>The iris flower dataset is available in <code>sklearn</code>. See, for example, <a href="https://scikit-learn.org/stable/datasets/index.html#iris-plants-dataset" rel="nofollow noreferrer">Iris plants dataset</a>.</p>
  
  <p><em>To search for other datasets, you can also use <a href="https://toolbox.google.com/datasetsearch" rel="nofollow noreferrer">https://toolbox.google.com/datasetsearch</a>.</em></p>
  
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Answers.UserDisplayName: nbro
Answers.Body: <p>After almost three years the question is still relevant. </p>
  
  <p>Let me add some too:</p>
  
  <p><a href="http://deeplearning.net/datasets/" rel="nofollow noreferrer">Deep Learning Datasets</a></p>
  
  <p>The datasets from the above link can be used for benchmarking deep learning algorithms.</p>
  
  <p><a href="https://cs.stanford.edu/~acoates/stl10/" rel="nofollow noreferrer">STL-10 dataset</a></p>
  
  <p>An image dataset which is inspired by <a href="http://www.cs.toronto.edu/~kriz/cifar.html" rel="nofollow noreferrer">CIFAR-10 dataset</a></p>
  
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Answers.UserDisplayName: naive
Body: <p>I have implemented an MLP. Now, I want to train it to solve simple tasks. </p>
  
  <p>Are there any data sets to train the MLP on simple tasks, that is, tasks with a small number of inputs and outputs? </p>
  
  <p>I would like to train it to solve problems which are slightly more complex than the XOR problem.</p>
  
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Comments.CreationDate: 2021-01-13T14:21:51.137Z
Comments.Text: Questions that ask for datasets are generally off-topic here. The most appropriate site to ask this type of question is probably Open Data SE.
Comments.UserDisplayName: nbro
Tags: <neural-networks><machine-learning><datasets><multilayer-perceptrons>
Title: What are some datasets to train an MLP on simple tasks?
UserDisplayName: David Price
ThreadText: # What are some datasets to train an MLP on simple tasks?
  
  (Asked by: username_0 on 2016-10-11)
  
  I have implemented an MLP. Now, I want to train it to solve simple tasks.
  
  Are there any data sets to train the MLP on simple tasks, that is, tasks with a small number of inputs and outputs?
  
  I would like to train it to solve problems which are slightly more complex than the XOR problem.
  
  **Tags:** neural-networks, machine-learning, datasets, multilayer-perceptrons
  
  > **Comments:**
  > **username_1**: Questions that ask for datasets are generally off-topic here. The most appropriate site to ask this type of question is probably Open Data SE.  
  
  ---
  
  ## 4 answers
  
  ### Answer by username_2 on 2016-10-13. Score: 4
  
  There are a ton of sample datasets our there you can play with. A bunch of good ones install with R in the datasets package. Luckily you can download them independently if you're not an R user. Try <https://vincentarelbundock.github.io/Rdatasets/datasets.html>
  
  You might also be interested in the [MNIST database](http://yann.lecun.com/exdb/mnist/) which is one of the canonical databases used in handwriting recognition research.
  
  Beyond that, you can look at / ask on <http://datasets.reddit.com> and/or <http://opendata.reddit.com> and you'll find all sorts of useful datasets.
  
  And finally, don't overlook the [UCI Machine Learning Repository](http://archive.ics.uci.edu/ml/).
  
  
  ---
  
  ### Answer by username_3 on 2016-10-11. Score: 2
  
  A popular dataset is the fisher iris dataset. It consists of 150 samples each with a dimensionality of 4. You can find it at
  <http://archive.ics.uci.edu/ml/datasets/Iris>
  
  
  ---
  
  ### Answer by username_1 on 2019-08-03. Score: 1
  
  If you want to solve a [multi-class classification](https://en.wikipedia.org/wiki/Multiclass_classification) problem, you could use the famous [iris flower dataset](https://en.wikipedia.org/wiki/Iris_flower_data_set), which was [introduced by Fisher in 1936](https://archive.ics.uci.edu/ml/datasets/iris). In this dataset, each flower has (only) $4$ features (the inputs), namely
  
  * petal length,
  * petal width,
  * sepal length, and
  * sepal width
  
  There are $3$ classes (the outputs)
  
  * iris setosa,
  * iris virginica, and
  * iris versicolor
  
  And there are a total of $150$ observations (or records).
  
  The iris flower dataset is available in `sklearn`. See, for example, [Iris plants dataset](https://scikit-learn.org/stable/datasets/index.html#iris-plants-dataset).
  
  *To search for other datasets, you can also use <https://toolbox.google.com/datasetsearch>.*
  
  
  ---
  
  ### Answer by username_4 on 2019-08-03. Score: 0
  
  After almost three years the question is still relevant.
  
  Let me add some too:
  
  [Deep Learning Datasets](http://deeplearning.net/datasets/)
  
  The datasets from the above link can be used for benchmarking deep learning algorithms.
  
  [STL-10 dataset](https://cs.stanford.edu/~acoates/stl10/)
  
  An image dataset which is inspired by [CIFAR-10 dataset](http://www.cs.toronto.edu/~kriz/cifar.html)
  
  
  ---
  
  