Github user chiwanpark commented on a diff in the pull request: https://github.com/apache/flink/pull/861#discussion_r37390659 --- Diff: docs/libs/ml/statistics.md --- @@ -0,0 +1,98 @@ +--- +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 +"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 statistics utility provides features such as building histograms over data, determining + mean, variance, gini impurity, entropy etc. of data. + +## Methods + + The Statistics utility provides two major functions: `createHistogram` and `dataStats`. + +### 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]. + 2. A continuous histogram can be formed by calling `X.createHistogram(b)` where `b` is the + number of bins. + **Discrete Histograms**: These histograms are formed on a data set `X:DataSet[Double]` + when the values in `X` are from a discrete distribution. These histograms + support `count(c)` operation which returns the number of elements associated with cateogry `c`. + <br> + A discrete histogram can be formed by calling `MLUtils.createDiscreteHistogram(X)`. + +### Data Statistics + + The `dataStats` function operates on a data set `X: DataSet[Vector]` and returns column-wise + statistics for `X`. Every field of `X` is allowed to be defined as either *discrete* or + *continuous*. + <br> + Statistics can be evaluated by calling `DataStats.dataStats(X)` or + `DataStats.dataStats(X, discreteFields`). The latter is used when some fields are needed to be --- End diff -- Wrong position of backtick symbol. \`DataStats.dataStats(X, discreteFields)\`
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