IBM SPSS Modeler

SPSS Modeler is a leading visual data science and machine learning solution. It helps enterprises accelerate time to value and achieve desired outcomes by speeding up operational tasks for data scientists. Leading organizations worldwide rely on IBM for data preparation and discovery, predictive analytics, model management and deployment, and machine learning to monetize data assets. SPSS Modeler empowers organizations to tap into data assets and modern applications, with complete algorithms and models that are ready for immediate use. It’s suited for hybrid environments to meet robust governance and security requirements and is available in IBM Watson Studio. SPSS Modeler helps you:

♦ Take advantage of open source-based innovation, including R or Python

♦ Empower data scientists of all skills — programmatic and visual

♦ Explore a hybrid approach — on-premises and in the public or private cloud

♦ Start small and scale to an enterprise-wide, governed approach

Key Features

Support for many data sources.

SPSS® Modeler can read data from flat files, spreadsheets, major relational databases, IBM Planning Analytics, and Hadoop. You can extend the capabilities of SPSS Modeler to the Analytic Server with our perpetual license.


Automatic data preparation.

SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields, and derive new attributes.

Visual analysis streams.

SPSS modeler provides an intuitive graphical interface to help visualize each step in the data mining process as part of a stream. Now analysts and business users can easily add expertise and business knowledge to the process.

A range of algorithmic methods.

SPSS Modeler offers multiple machine learning techniques — including classification, segmentation and association algorithms including out-of-the-box algorithms that leverage Python and Spark. Users can now employ languages such as R and Python to extend modeling capabilities.

Geospatial analytics.

Explore geographic data such as latitude and longitude, postal codes, and addresses using SPSS Modeler. By combining that information with current and historical data you can generate better insights and improve predictive accuracy.

Machine learning methods and algorithms.

SPSS Modeler supports decision trees, neural networks, and regression models. Now you can take advantage of ARMA, ARIMA and exponential smoothing; transfer functions with predictors and outlier detection; benefit from the ensemble and hierarchical models; support vector machine and temporal causal modeling; and employ time series and spatial AR for spatiotemporal prediction. Generative adversarial networks (GANs) and reinforcement also enable deep learning.

Easy model deployment.

From Scikit-learn and Tensorflow to SPSS Modeler, save and deploy models from the most popular machine learning frameworks using the tools of your choice: including notebooks and Modeler Flows in Watson Studio Desktop or any IDE used for Python.

Powerful graphics engine.

Leverage Watson Studio Desktop’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations.

Automated modeling.

SPSS Modeler can test multiple modeling methods, compare results and select which model to deploy in a single run. This enables you to quickly choose the best performing algorithm based on model performance.

Text analytics.

SPSS Modeler captures key concepts, themes, sentiments and trends by analyzing unstructured text data. Now you can uncover valuable insights in blog content, customer feedback, emails and social media comments.

Support for open-source technologies.

SPSS Modeler enables the use of R, Python, Spark, and Hadoop to amplify the power of analytics. You can also extend and complement these technologies for more advanced analytics while maintaining control. SPSS Modeler Gold includes access to Watson Studio Desktop, which allows you to extend your Modeler streams with Jupyter Notebooks, enabling line of business users and data scientists to collaborate on the same platform.

Multiple deployment methods.

IBM SPSS Modeler is also available as part of IBM Watson Studio, as well as the perpetual offering. Using Modeler Gold, data scientists can schedule jobs to run at desired times. IT administrators can integrate deployment into existing systems for batch, real-time or streaming.

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