IBM SPSS Modeler Premium V18.1 Student GradPack Click on images to enlarge
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IBM SPSS Modeler Premium V18.1 Student GradPack - For Students Only

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

Part#: D0EW4LL-18

IBM SPSS Modeler Premium V18 Student GradPack an extensive predictive analytics platform, designed to bring predictive intelligence to decision making. Find hidden relationships in data, using data and text mining. This software provides students with a range of advanced algorithms and techniques, including text analytics, entity analytics, decision management and optimization. These features help you unlock important insights from almost any type of data. Explore the impact of classification, segmentation and association.

Features of IBM SPSS Modeler Premium V18 Student GradPack

By integrating predictive analytics with decision management, SPSS Modeler helps students understand the impact of making the right decision based on data analytics. The Modeler Premium Grad Pack features a range of tools to help you make the right decision every time!

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.
  • 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.

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