Sorority Initiation Planning

Algorithms for Data Mining with SQL Server 2008

A few weeks ago talking with a friend on Data mining and made me question that echo many of us have at some point in our learning .. When I use this or that algorithm and in what cases? ... I always said "it depends" and then go back to reading Microsoft Technet for SSAS was reading what I put below by way of a Copy & Paste the info to Microsoft.

The data mining models can predict values, generate summaries data and find hidden correlations. To help you select the algorithms for data mining solution, the following table provides suggestions about what algorithms to use for specific tasks.

Microsoft use

Task	algorithms that can be
Predicting discrete attribute. For example, to predict whether the target of a campaign of direct mail will become a product.	Algorithm Microsoft Decision Trees Algorithm Microsoft Naive Bayes Microsoft Clustering Algorithm (Analysis Services - Data Mining) neural network algorithm Microsoft (Analysis Services - Data Mining)
Predicting a continuous attribute. For example, forecast sales next year.	Algorithm Microsoft Decision Trees Algorithm Microsoft Time Series (Analysis Services - Data Mining)
Predicting a sequence. For example, clickstream analysis of a company website.	Clustering Algorithm Microsoft sequence
Search groups common elements transactions. For example, using the analysis of the basket to suggest to a customer to buy additional products.	Microsoft Association Algorithm Algorithm Microsoft Decision Trees
Search groups of similar items. For example, target demographic group to better understand the relationships between attributes.	Microsoft Clustering Algorithm (Analysis Services - Data Mining) clustering algorithm sequence Microsoft