.. _Subject_Index:

Index By Subject
================

**Algorithms Roadmap**

  * :ref:`Roadmap`

**Benchmarks**

* :ref:`Benchmark`
 
**Classification**


  * :ref:`RFmath`
  * :ref:`NBmath`
  * :ref:`KMmath`

**Data Science** 

   * :ref:`Data_Science`

**Data**
 
  * :ref:`SUMmath`

**Deep Learning**

  * :ref:`DLmath`

**Development**

  * :ref:`Developer`

**Downloads**

  * :ref:`GettingStartedFromaZipFile`

**Eclipse**

  * :ref:`Eclipse`

**Generalized Linear Modeling**

  * :ref:`GLMmath`
  * :ref:`GLM_tutorial`

**Gradient Boosted Models**

  * :ref:`GBMmath`
  * :ref:`GLMgrid_tutorial`

**Hadoop**

  * :ref:`Hadoop`
  * :ref:`MacHadoop`

**High Availability**

  * :ref:`HA`

**Idea**

  * :ref:`Idea`

**Java**

  * :ref:`Java`
  * :ref:`Javahelp`

**K-Means**

 * :ref:`KMmath`
 * :ref:`KM_tutorial`

**Machine Learning**

  * :ref:`Machlearn`

**Multinode**

  * :ref:`Multinode`

**Naive Bayes**

  * :ref:`NBmath`

**Principal Components Analysis**
  
  * :ref:`PCAmath`

**R**

  * :ref:`R_user`

**R Package Document**

  * :ref:`R_pdf`

**Random Forest**
  
  * :ref:`RFmath`

**References**

  * :ref:`References`

**Scala**

**Stochastic Gradient Descent** 

  * :ref:`SGDmath`

**Summary (summary statistics on data)**

  * :ref:`SUMmath`

**Tutorials**

  * :ref:`GLM_tutorial`
  * :ref:`GLMgrid_tutorial`
  * :ref:`KM_tutorial`