Clementine server a data mining software for business solution
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Clementine Server A data mining software for business solution. What is Clementine Server. Clementine Server is a large scale, distributed Data mining software package with  fast and scalable performance,  user-friendly visual workflow interface,  powerful analytical techniques. .

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Clementine Server A data mining software for business solution

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Clementine ServerA data mining software for business solution


What is Clementine Server

Clementine Server is a large scale, distributed Data mining software package with

fast and scalable performance,

user-friendly visual workflow interface,

powerful analytical techniques.

.


Brief Introduction to Clementine

History of Clementine Series:

  • Clementine Series was initiated by Integral Solutions Ltd in 1994.

  • SPSS took over ISL in 1998.

  • SPSS introduced the latest version - Clementine Server 5.1 with distributed architecture in earlier 1999.

    Old version vs New version:

    Stand-alone application architecture

    vs

    Distributed architecture


Architecture

Stand-alone application architecture


Architecture

Distributed Architecture


Capabilities

Fast and scalable Performance with Distributed Architecture


Capabilities

Interactive and efficient mining process with Visual Workflow Interface

 Visual Programming

  • Enables non-technical users to solve business problems.

     Easy & Intuitive desktop

  • Allows rapid experimentation, and creative development of models.


Palette forGeneratedModels

Desktop

ObjectPalette


Clementine will report the predicted accuracy of the two

used algorithms: neural network and rule induction.


The target data will run through the model to produce knowledge

Data Source

Useful Knowledge


Capabilities

Multiple model building techniques:

- Rule Induction

- Graph

- Clustering

- Association Rules

- Linear Regression

- Neural Networks


Functionalities

 Classification

Rule Induction, neural Networks

 Association

Rule Induction, Apriori

 Clustering

Kohonen Networks, Rule Induction

 Sequence

Rule Induction, Neural Networks, LinearRegression

 Prediction

Rule Induction, Neural Networks


Applications

 Predict market share

 Detect possible fraud

 Locate new retail sites

 Assess financial risk

 Analyze demographic trends and patterns


Limitation

 Clementine does not have effective incremental

methods to update mining results.

 Clementine does not support certain data sources

i.e. Dbase, Foxpro.


Summary

  • Clementine Server

    Fast and scalable performance on large datasets

    - unique distributed architecture

    Rapid and creative development of models

    - user-friendly visual workflow interface

    Multiple applications

    - various modeling techniques


 Peng Wang

 Chong Zhang

 Hang Cui

Clementine Study Group


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