IBM SPSS Modeler

Solve your toughest challenges with data mining

IBM SPSS Modeler Professional and IBM SPSS Modeler Premium is available in both a desktop-based client deployment as well as a client/server deployment model. The features shown in the chart below are accessed from the client. IBM SPSS Modeler Server, available as both a Professional and Premium edition, provides server-based processing and performance enhancement as well as additional features such as batch processing, SQL pushback and in-database mining.

  Modeler Professional Modeler Premium
Create a wide range of interactive graphs with automatic assistance X X
Use visual link analysis to see the associations in your data X X
Interact with data by selecting regions or items on a graph and view the selected information; or select key data for use in analysis X X
Access IBM SPSS Statistics tools directly from interface X X
Read from and write to operational data from a variety of operational datasources such as IBM DB2®, Oracle®, Microsoft SQL Server™, Informix®,  Neoview, Netezza, mySQL (Sun) and Teradata. X X
Read from and write to data views and metadata stored in Cognos® 8 Business Intelligence X X
Import from and export to delimited and fixed-width text files, any IBM SPSS Statistics file, SAS, IBM Data Collection data sources, or XML X X
Data-cleaning options that remove or replace invalid data, automatically impute missing values and mitigate for outliers and extremes X X
Apply automatic data preparation to interrogate and condition data for analysis in a single step X X
Field filtering, naming, derivation, binning, re-categorization, value replacement, and field reordering X X
Record selection, sampling (including clustered and stratified sampling), merging (including inner joins, full outer joins, partial outer joins, and anti-joins), and concatenation; sorting, aggregation, and balancing X X
Data restructuring, partitioning and transposition X X
Extensive string functions: string creation, substitution, search and matching, whitespace removal, and truncation X X
RFM scoring: aggregate customer transactions to provide Recency, Frequency, and Monetary value scores and combine these to produce a complete RFM analysis. X X
Use interactive model and equation browsers and view advanced statistical output X X
Show relative impact of different data attributes on predicted outcomes with variable importance graphs X X
Combine multiple models or use one model to analyze a second model X X
Use automatic classification (both binary and numeric) and clustering models to eliminate need for selecting individual algorithm X X
Use Modeler’s Component-Level Extension Framework (CLEF) to build custom algorithms X X
Through the integration of IBM SPSS Statistics, use R to extend analysis options through customization X X
C&RT, CHAID & QUEST—Decision tree algorithms including interactive tree building X X
Decision List—Interactive rule-building algorithm X X
K-Means, Kohonen, Two Step, Discriminant, Support Vector Machine (SVM) — Clustering and segmentation algorithms X X
GRI—Generalized rule induction association discovery algorithm X X
Factor/PCA, Feature Selection—Data reduction algorithms X X
Regression, Linear, GenLin (GLM)—Linear equation modeling  X X
Self-learning response model (SLRM)—Bayesian model with incremental learning X X
Time-series—Generate and automatically select time-series forecasting models X X
C5.0 decision tree and rule set algorithm X X
Neural Networks—Multi-layer perceptrons with back-propagation learning, and radial basis function networks X X
Support Vector Machines—Advanced algorithm with accurate performance for wide datasets X X
Bayesian Networks—graphical probabilistic models X X
Cox regression—calculate likely time to an event X X
Anomaly Detection—Detect unusual records through the use of a cluster-based algorithm X X
KNN – Nearest neighbor modeling and scoring algorithm X X
Apriori—Popular association discovery algorithm with advanced evaluation functions X X
CARMA—Association algorithm which supports multiple consequents X X
Sequence—Sequential association algorithm for order-sensitive analyses X X
Export models using SQL or PMML (the XML-based standard format for predictive models) X X
 Extract text data from files, operational databases and RSS feeds (ie. blogs, web feeds) X
Select native language extractor options for Dutch, English, French, German, Italian, Portuguese, Spanish or Japanese or translate virtually any language using Language Weaver (separately licensed) X
Extract domain-specific concepts such as uniterms, expressions, abbreviations, acronyms, and more X
 Calculate synonyms using sophisticated linguistic algorithms and embedded or user-specified linguistic resources X
 Name concepts by person, organization, term, product, location, and other user- defined types X
 Extract non-linguistic entities such as address, currency, time, phone number, and social security number (SSN) X
Use and customize pre-built templates and libraries for sentiment analysis, CRM, security and intelligence, market intelligence, life sciences, and IT X
 Leverage pre-packaged Text Analytics Packages (TAPs) for the most common business applications and create your own X
Create clusters based on term co-occurrence using concept clustering algorithms, which provide an at-a-glance view of main topics and the way in which they are related X
Intelligently group text documents and records based on content, using text classification algorithms –Enable advanced concept selection and deselection for use in predictive modeling X
Use text based and visual reports to interrogate concept relationship, occurrence, frequency and type X
 Identify and extract sentiments (for example, likes and dislikes) from text in Dutch, English, French, German, and Spanish X
Ability to read from IBM Classic Federation data sources X X