IBM SPSS Modeler Premium v18.1 Faculty Pack Click on images to enlarge
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IBM SPSS Modeler Premium v18.1 Faculty Pack - For Faculty Only

(12 Month Fixed Term Download, Academic Authorized User, Multilingual)

Part#: D0EVULL-18

IBM SPSS Modeler Premium Faculty Pack allows you to find hidden relationships in data, using data and text mining. It also includes Modeler Premium, which delivers comprehensive data mining and text analytics tools. IBM SPSS Modeler Premium provides a range of advanced algorithms and techniques that help individuals, groups, systems and enterprises make informed decisions. Unlock insights from almost any type of data!

Features of IBM SPSS Modeler Premium Faculty Pack

Analytical decision management

Automate and optimize transactional decisions by combining predictive analytics, rules and scoring to deliver recommended actions in real time. Decision management capabilities enable the integration of predictive analytics and business rules into an organization’s processes to optimize and automate high-volume decisions at the point of impact.

Automated modeling

Use a variety of modeling approaches in a single run and then compare the results of the different modeling methods. Select which models to use in deployment, without having to run them all individually and then compare performance. Choose from three automated modeling methods: Auto Classifier, Auto Numeric and Auto Cluster.

Text analytics

Go beyond the analysis of structured numerical data and include information from unstructured text data, such as web activity, blog content, customer feedback, emails and social media comments. Capture key concepts, themes, sentiments and trends and ultimately improve the accuracy of your predictive models.

Entity analytics

Identity resolution is vital in a number of fields, including customer relationship management, national security, fraud detection and prevention of money laundering. Entity analytics improves the coherence and consistency of data by resolving like entities even when the entities do not share any key values.

Social network analysis

Social network analysis examines the relationships between social entities and the implications of these relationships on an individual’s behavior. It is particularly useful for those in telecommunications and other industries concerned about attrition (or churn). By identifying groups, group leaders and whether others will be affected based on influence, predictive models can be built on an individual and enhanced with their group and social behavior data.

Geospatial analytics

Geospatial analytics explore the relationship between data elements that are tied to a geographic location. When combined with current and historical data, information such as latitude and longitude, postal codes and addresses can reveal deeper insights about people and events and improve predictive accuracy. Geospatial analytics is frequently used in fields such as disease surveillance, law enforcement and building and facilities management.

Modeling algorithms

The modeling algorithms included in SPSS Modeler are:

  • Anomaly Detection. Detect unusual records with a cluster-based algorithm.
  • Apriori. Identify the frequent individual items in your transactional databases and extend them to larger item sets.
  • Bayesian Networks. Estimate conditional dependencies with graphical probabilistic models that combine the principles of graph theory, probability theory, computer science and statistics.
  • C&RT, C5.0, CHAID and QUEST. Generate decision trees, including interactive trees.
  • CARMA. Mine for association rules with support for multiple consequents and continuous feedback for deterministic and accurate results.
  • Cox regression. Calculate likely time to an event.
  • Decision List. Build interactive rules.
  • Factor/PCA, Feature Selection. Reduce data.
  • Generalized Spatial Association Rule: Find patterns/association rules where location matters.
  • K-Means, Kohonen, Two Step, Discriminant, Support Vector Machine (SVM). Cluster and segment data.
  • KNN. Model and score nearest neighbor.
  • Logistic Regression. Generate binary outcomes.
  • Neural Networks. Take advantage of multilayer perceptrons with back-propagation learning and radial basis function networks.
  • Regression, Linear, GenLin (GLM), Generalized Linear Mixed Models (GLMM). Model linear equations.
  • Self-learning response model (SLRM). Take advantage of a Bayesian model with incremental learning.
  • Sequence. Conduct order-sensitive analysis with sequential association algorithm.
  • Spatial-Temporal Prediction (STP). Predict how a place will change over time.
  • Support Vector Machine. Apply non-linear functions based on computational learning theory for efficient learning on wide datasets.
  • Time-series. Generate and automatically select time-series forecasting models using techniques such as temporal causal modeling, which discovers causal relationships among large numbers of series.
  • Two-step clustering: Identify data points by similarity and group them into clusters.

SPSS Modeler Desktop System Requirements

For the system requirements for SPSS Modeler include operating system and hardware requirements please - click here.

An SPSS Faculty Pack is restricted to use by a Faculty Member, which is an individual who actively teaches a course utilizing IBM SPSS Programs for a degree granting institution, for classroom teaching and non-commercial academic research. Non-commercial academic research means research by a Faculty Member where (i) the results of such research are not intended primarily for the benefit of a third party; (ii) such results are made available to anyone without restriction on use, copying or further distribution; and (iii) any copy of any such result is furnished for no more than the cost of reproduction and shipping. Any other use including but not limited to university administration and operations is strictly prohibited.

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