Advanced Data Preparation Using IBM SPSS Modeler (V16)
Descripción: Curso Advanced Data Preparation Using IBM SPSS Modeler (V16)
Formación en IBM Analytics
Advanced Data Preparation Using IBM SPSS Modeler (V16) covers advanced topics to aid in the preparation of data for a successful data mining project. You will learn how to use functions, deal with missing values, use advanced field operations, handle sequence data, apply advanced sampling methods, and improve efficiency.
Use the Transform node to change a field's distribution
Working with Sequence Data
Use cross-record functions
Use the Count mode in the Derive node
Use the Restructure node to expand a continuous field into a series of continuous fields
Use the Space-Time-Boxes node to work with geospatial and time data
Use the Sample node to draw simple and complex samples
Draw complex samples
Partition the data into a training and a testing set
Reduce or boost the number of records
Use database scalability by SQL pushback
Use the Data Audit node to process outliers and missing values
Use the Set Globals node
Use looping and conditional execution
This advanced course is for IBM SPSS Modeler Analysts and IBM SPSS Modeler Data Experts who want to become familiar with the full range of techniques available in IBM SPSS Modeler for data manipulation.
You should have:
General computer literacy.
Some experience using IBM SPSS Modeler including familiarity with the Modeler environment, creating streams, reading data files, and doing simple data exploration and manipulation using the Derive node.
Prior completion of Introduction to IBM SPSS Modeler and Data Mining (V16) is recommended.
Please refer to Course Overview for description information.