Industry News

Frontline Systems releases XLMiner SDK V2018 for high-performance predictive analytics

Frontline Systems has released XLMiner SDK V2018, a next-generation version of its Software Development Kit for data mining, text mining, forecasting and predictive analytics. XLMiner SDK offers application developers working in C++, C#, Java, Python or R a powerful, high-level API for quickly creating applications that use predictive analytics.

“Data mining and machine learning software has proliferated, but there’s a difference between common libraries and truly robust, high-performance software – especially if you’re working in C++, C# or Java,” says Daniel Fylstra, Frontline’s president and CEO. “XLMiner SDK is a toolkit that developers can count on to build commercial-grade applications.”

XLMiner SDK provides full API support for five popular programming languages: C++ 11 or later, C# 4.0 or later, Java 8, Python 2.7 or 3.6 (both are supported), and R 3.4. In Microsoft Visual Studio and R Studio, developers will benefit from automatic recognition and “command completion” for XLMiner’s objects, properties and methods. And the new SDK is ready for REPL (Read-Eval-Print-Loop) style execution with C# Interactive.

XLMiner SDK’s R support uses R-native types, including R’s own DataFrame type; hence it can be used easily with a wide range of R packages from CRAN. XLMiner SDK provides its own “R package” that can be loaded with one command from R itself or an IDE such as R Studio.

For C++, C# and Java developers, XLMiner SDK should be especially welcome, since quality data mining tools have been hard to find for these popular languages. But even R and Python developers will find that XLMiner SDK offers a far better integrated, comprehensive data mining and text mining toolkit.

XLMiner SDK has built-in tools to read data from SQL databases using ODBC (Open Data Base Connectivity), with special support for Oracle, Microsoft SQL Server and Access databases; OData (“the web successor to ODBC”) data sources exposing a REST API; JSON (JavaScript Object Notation); and CSV (Comma Separated Value) and Excel files.

The SDK also handles unstructured text data and provides stemming, term normalization, vocabulary reduction, creation of a term-document matrix, and concept extraction with latent semantic indexing. It even has built-in facilities to draw a statistically representative sample from an Apache Spark Big Data cluster, running a Frontline-supplied component on one of the cluster nodes.

Thompson Street Capital Partners makes significant investment in Gurobi Optimization

Gurobi Optimization, LLC (Gurobi), provider of a leading math programming solver, announced that Thompson Street Capital Partners (TSCP), a private equity firm based in St. Louis, has made a significant financial investment in Gurobi to help it to continue its growth as a leader in the rapidly expanding prescriptive analytics space. Terms of the deal were not announced.

Gurobi’s commitment to industry-leading performance, ease of use and customer support have made the Gurobi Optimizer today’s solver of choice for more than 1,500 companies in more than 40 industries. Used in mission-critical applications or as a distributed optimization service, Gurobi allows users to state their toughest business problems as mathematical models, and then automatically considers billions – or even trillions – of possible solutions to find the best one. Thompson Street’s investment allows Gurobi to further accelerate growth while maintaining its focus on customer success.

“We’re very excited about the opportunities that come with working with Thompson Street,” says Ed Rothberg, CEO and co-founder of Gurobi. “This investment gives us access to both the capital and business expertise to stay focused on our users’ needs today while developing the capabilities they will want in the future.”

Craig Albrecht, managing director, TSCP says, “We like to partner with companies that are already industry leaders with proven go-to-market strategies. We are thrilled to partner with Gurobi’s superb leadership team to help them accelerate the company’s already outstanding growth without losing sight of what has made the company so successful.”

AIMMS adds ODH-CPLEX to its Prescriptive Analytics Platform

AIMMS announce that it has formed an agreement with Optimization Direct to include their new product, ODH-CPLEX, in the AIMMS Prescriptive Analytics Platform as an available add-on.

The AIMMS Prescriptive Analytics Platform is the technology of choice for operations research and analytics professionals to build and deliver solutions that improve business performance. The Platform leverages the power of mathematical optimization and modeling to provide companies with a competitive edge and quantifiable results. AIMMS has been doing this for nearly three decades, and always tries to find innovative ways to improve value for customers.

Large-scale optimization enables decision-makers to evaluate scenarios in any part of the business. For example, supply chain organizations can use optimization for production planning and scheduling, supply chain management, sourcing, etc. As complexity and data volumes increase, the need for more powerful optimizers (so-called mathematical solvers) also increases. Optimization Direct is focusing on improving the performance of optimizers, specifically CPLEX, by offering additional mathematical “horsepower” to solve the largest and most complex planning, scheduling and supply chain optimization problems. ODH-CPLEX is a new solver designed to run on modern multiprocessor machines.

“We decided to add ODH-CPLEX in our suite because the product meets the needs in specific situations where our customers require an even higher performance from CPLEX. It is a great and easy way to generate value quickly,” says Gertjan de Lange, SVP Connecting Business & Optimization at AIMMS. “We have worked very closely with Optimization Direct to get the best performance from ODH-CPLEX. Their support is superb, and they allow us to set a new bar in the world of prescriptive analytics technology.”