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From sachingoel0101 <...@git.apache.org>
Subject [GitHub] flink pull request: [FLINK-2030][FLINK-2274][ml]Online Histograms ...
Date Thu, 20 Aug 2015 13:20:13 GMT
Github user sachingoel0101 commented on a diff in the pull request:

    --- Diff: docs/libs/ml/statistics.md ---
    @@ -0,0 +1,69 @@
    +mathjax: include
    +htmlTitle: FlinkML - Statistics
    +title: <a href="../ml">FlinkML</a> - Statistics
    +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
    +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
    +## Description
    + The statistics utility provides features such as building histograms over data.
    +## Methods
    + The Statistics utility provides two major functions: `createHistogram` and
    + `createDiscreteHistogram`.
    +### Creating a histogram
    + There are two types of histograms:
    +   1. **Continuous Histograms**: These histograms are formed on a data set `X: DataSet[Double]`
    +   when the values in `X` are from a continuous range. These histograms support
    +   `quantile` and `sum`  operations. Here `quantile(q)` refers to a value $x_q$ such
that $|x: x
    +   \leq x_q| = q * |X|$. Further, `sum(s)` refers to the number of elements $x \leq s$,
which can
    +    be construed as a cumulative probability value at $s$[Of course, *scaled* probability].
    --- End diff --
    The idea is, histograms are meant to represent a probability distribution, and there is
a very clear correspondence. A probability mass function corresponds to a discrete valued
histogram and a probability density function corresponds to a continuous valued histogram.

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