Data mining with oracle using classification and clustering algorithms
Download
1 / 10

Data Mining with Oracle using Classification and Clustering Algorithms - PowerPoint PPT Presentation


  • 139 Views
  • Uploaded on

Data Mining with Oracle using Classification and Clustering Algorithms. Presented by Nhamo Mdzingwa Supervisor: John Ebden. Overview of Presentation. Recap of Proposal Classification of Data Mining & DM Algorithms Oracle Data Mining Data Mining Process Evaluation of Results

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Data Mining with Oracle using Classification and Clustering Algorithms' - megan-cabrera


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Data mining with oracle using classification and clustering algorithms

Data Mining with Oracle using Classification and Clustering Algorithms

Presented by Nhamo Mdzingwa

Supervisor: John Ebden


Overview of presentation
Overview of Presentation Algorithms

  • Recap of Proposal

  • Classification of Data Mining & DM Algorithms

  • Oracle Data Mining

  • Data Mining Process

  • Evaluation of Results

  • Progress so far

  • Updated Timeline

  • Plans


Objective
Objective Algorithms

  • Investigate two types of algorithms available in Oracle10g for data mining (ODM).

  • Apply the two algorithms to actual data.

    • Analyse &

    • Evaluate results in terms of performance.


Classification of data mining
Classification of Data Mining Algorithms

  • Directed data mining/supervised learning

    which build a model that describes one particular attribute in terms of the rest of the data.

  • Undirected DM / Unsupervised learning

    builds a model to establish the relationships amongst all the input attributes by grouping.


Classification of data mining algorithms

Input attributes but have no output attributes Algorithms

Input attributes and output one or more attributes

Classification of Data Mining algorithms

DM strategies

Unsupervised learning

Supervised learning

Classification

Naive Bayes

Model Seeker

Adaptive Bayes

Clustering

k-Means

O-Cluster

Estimation

Association Discovery

Prediction

Predictive variance

Visualization


Algorithms offered in oracle10g
Algorithms offered in Oracle10g Algorithms

classification

  • Adaptive Bayes Network

  • Naive Bayes

  • Model Seeker

    clustering

  • k-Means

  • O-Cluster

  • Predictive variance

    association rules

  • Apriori (association rules)


Evaluation of results
Evaluation of Results Algorithms

  • Evaluation of unsupervised learning models involves determining the level of predictive accuracy.

  • Evaluated using test data sets.

  • Compare confidence and support levels of models created from the same training data to determine accuracy.


Progress
Progress Algorithms

  • Literature Survey

  • Oracle10g installed on Athena in Hons Lab

  • Exploring the Oracle9i and 10g Suite including JDeveloper

  • Member of MetaLink (Oracle’s online support service)


Updated timeline
Updated Timeline Algorithms


ad