maica.util
==========
The ``maica.util`` module includes useful functions for preprocessing and visualization.
This can be used to convert a user dataset into a new dataset suitable for machine learning.
Also, it can be applied to analyze prediction results of machine learning.
In addition to the supplementary functions, this module provides meta-heuristic algorithms for optimizing
the input data of the mathematical functions and machine learning models.


**Functions**

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   :widths: 30 70
   :header-rows: 1

   * - Function Name
     - Description
   * - impute
     - Fill empty values in the given dataset.
   * - get_split_idx
     - Randomly generate two subsets of the original indices. This function is useful to split a dataset into training and test datsaets.
   * - get_one_hot_feat
     - Generate one-hot encoding of the categorical features.
   * - get_target_dist
     - Get a histogram of the target values. Lists of the bins and the labels of the histogram are returned for the given target values.
   * - get_error_dist
     - Compute mean of the prediction errors for each range of target values.
   * - plot_target_dist
     - Plot a histogram of the target values for a given dataset.
   * - plot_error_dist
     - Plot a distribution of prediction errors for each range of target values.
   * - plot_pred_result
     - Draw a scatter plot of target and predicted values.
   * - plot_embeddings
     - Draw a 2-dimensional scatter plot of data embeddings.
   * - optimize
     - Find the optimal input of a given objective function.
   * - run_ml_model
     - A wrapper function to run machine learning algorithms for meta-heuristic based input optimization.


.. automodule:: util.preprocessing
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   :undoc-members:

.. automodule:: util.analysis
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.. automodule:: util.visualization
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   :undoc-members:

.. automodule:: util.optimization
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   :undoc-members: