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From hhbyyh <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-8531] [ML] Update ML user guide for Min...
Date Thu, 13 Aug 2015 02:06:34 GMT
Github user hhbyyh commented on a diff in the pull request:

https://github.com/apache/spark/pull/7211#discussion_r36935159

--- Diff: docs/ml-features.md ---
@@ -905,6 +906,74 @@ scaledData = scalerModel.transform(dataFrame)
</div>
</div>

+## MinMaxScaler
+
+MinMaxScaler transforms a dataset of Vector rows, rescaling each feature to a specific
range (often [0, 1]).  It takes parameters:
+
+* min: 0.0 by default. Lower bound after transformation, shared by all features.
+* max: 1.0 by default. Upper bound after transformation, shared by all features.
+
+MinMaxScaler computes summary statistics on a data set and produces a MinMaxScalerModel.
The model can then transform each feature individually such that it is in the given range.
+
+The rescaled value for a feature E is calculated as,
+
+  Rescaled(e_i) = \frac{e_i - E_{min}}{E_{max} - E_{min}} * (max - min) + min
--- End diff --

Sure, do you mean adding $$....$$, or I should further modify
the equation.

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