(Version 3) Online Help This help file will guide you in using XLMiner™ to analyze your business data. As you go through the file, you will get familiar with all the operations necessary for analyzing data with XLMiner. To read about a specific technique, click on the relevant link below. Each topic is explained with a brief introduction, followed by an example of how to use XLMiner to utilize the procedure. Order a printed copy of the used guide from On Demand Manuals.

2. Procedures 

• Partition Data
  • Standard Partition
  • Partition with Oversampling

 

• Data Utilities

  • Sample from Worksheet
  • Sample from Database (Only in Standard and Demo edition. Not present in Education Edition)
  • Missing Data Handling
  • Bin Continuous Data
  • Transform categorical Data

• Time Series 

• Prediction 

  • Multiple Linear Regression
  • k-Nearest Neighbors
  • Regression Tree
  • Neural Network (Multilayer feedforward)

• Classification

  • Discriminant Analysis
  • Logistic Regression
  • Classification Tree
  • Naive Bayes
  • Neural Network (Multilayer feedforward)
  • k-Nearest Neighbors

• Stored Model Sheets

   

• Affinity

  • Association Rules

• Data Reduction and Exploration

  • Principal Component Analysis
  • k-Means Clustering
  • Hierarchical Clustering

• Charts

  • Box Plot

  • Histogram

  • Matrix Plot

3. Data Handling Specifications

4. References