Github user fobeligi commented on a diff in the pull request: https://github.com/apache/flink/pull/798#discussion_r31894794 --- Diff: docs/libs/ml/minMax_scaler.md --- @@ -0,0 +1,113 @@ +--- +mathjax: include +htmlTitle: FlinkML - MinMax Scaler +title: <a href="../ml">FlinkML</a> - MinMax Scaler +--- +<!-- +Licensed to the Apache Software Foundation (ASF) under one +or more contributor license agreements. See the NOTICE file +distributed with this work for additional information +regarding copyright ownership. The ASF licenses this file +to you under the Apache License, Version 2.0 (the +"License"); you may not use this file except in compliance +with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, +software distributed under the License is distributed on an +"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +KIND, either express or implied. See the License for the +specific language governing permissions and limitations +under the License. +--> + +* This will be replaced by the TOC +{:toc} + +## 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>Std</strong></td> --- End diff -- Yes, you are right!
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