docs/libs/ml/min_max_scaler.md

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## Description

 The MinMax scaler scales the given data set, so that all values will lie between a user specified range [min,max].
 In case the user does not provide a specific minimum and maximum value for the scaling range, the MinMax scaler transforms the features of the input data set to lie in the [0,1] interval.
 Given a set of input data $x_1, x_2,... x_n$, with minimum value:

 $$x_{min} = min({x_1, x_2,..., x_n})$$

 and maximum value:

 $$x_{max} = max({x_1, x_2,..., x_n})$$

The scaled data set $z_1, z_2,...,z_n$ will be:

 $$z_{i}= \frac{x_{i} - x_{min}}{x_{max} - x_{min}} \left ( max - min \right ) + min$$

where $\textit{min}$ and $\textit{max}$ are the user specified minimum and maximum values of the range to scale.

## Operations

`MinMaxScaler` is a `Transformer`.
As such, it supports the `fit` and `transform` operation.

### Fit

MinMaxScaler is trained on all subtypes of `Vector` or `LabeledVector`:

* `fit[T <: Vector]: DataSet[T] => Unit`
* `fit: DataSet[LabeledVector] => Unit`

### Transform

MinMaxScaler transforms all subtypes of `Vector` or `LabeledVector` into the respective type:

* `transform[T <: Vector]: DataSet[T] => DataSet[T]`
* `transform: DataSet[LabeledVector] => DataSet[LabeledVector]`

## Parameters

The MinMax scaler implementation can be controlled by the following two parameters:

 <table class="table table-bordered">
  <thead>
    <tr>
      <th class="text-left" style="width: 20%">Parameters</th>
      <th class="text-center">Description</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td><strong>Min</strong></td>
      <td>
        <p>
          The minimum value of the range for the scaled data set. (Default value: <strong>0.0</strong>)
        </p>
      </td>
    </tr>
    <tr>
      <td><strong>Max</strong></td>
      <td>
        <p>
          The maximum value of the range for the scaled data set. (Default value: <strong>1.0</strong>)
        </p>
      </td>
    </tr>
  </tbody>
</table>

## Examples

{% highlight scala %}
// Create MinMax scaler transformer
val minMaxscaler = MinMaxScaler()
  .setMin(-1.0)

// Obtain data set to be scaled
val dataSet: DataSet[Vector] = ...

// Learn the minimum and maximum values of the training data
minMaxscaler.fit(dataSet)

// Scale the provided data set to have min=-1.0 and max=1.0
val scaledDS = minMaxscaler.transform(dataSet)
{% endhighlight %}