Only Analytic Solver will automatically fit user data to the full range of possible (bounded and unbounded, multi-term) Metalog distributions. Tom Keelin, that can closely approximate virtually any classical continuous distribution, and better fit historical data than classical distributions. In risk analysis and Monte Carlo simulation, Analytic Solver and RASON offer leading support for the increasingly popular Metalog family of distributions, created by Dr. Better Simulation Models with Metalog Distributions and Fitting The user simply supplies data in tabular form: Analytic Solver will test and evaluate multiple types of machine learning models – classification and regression trees, neural networks, linear and logistic regression, discriminant analysis, naïve Bayes, k-nearest neighbors and more, validate and compare them according to user-chosen criteria, and deliver the model that best fits the data. Automated Machine Learning with Find Best ModelĪnalytic Solver offers “augmented machine learning” features found only in other sophisticated machine learning tools. RASON in V2022 includes further enhancements to its ability to concurrently solve a wide range of models from many users and different sources.
These performance enhancements apply to both Analytic Solver Desktop, which solves models on users' own PCs, and to Analytic Solver Cloud, which solves models “in the cloud” via the RASON service. For larger models, this can cut end-to-end solution time by 50% or more. Higher Performance Optimizationīesides including the latest, fastest-ever versions of optimization solvers such as the Gurobi Solver 9.5 for linear, quadratic and mixed-integer problems, Analytic Solver V2022 offers fastest-ever performance in ‘model setup’ – the process of analyzing a model with complex, inter-linked formulas and use of Excel’s many built-in functions, and converting this into the relatively simple form that optimization solvers can use. Users can also deploy and share probability models, following the open Probability Management 3.0 standard – a major benefit for large organizations with multiple risk analysis and modeling projects.
These models can be used directly for classification and prediction (no auxiliary code such as R or Python needed), and they are easily managed, governed, and even run in multi-stage ‘decision flows’ with RASON’s facilities – gaining the benefits of Azure authentication and cybersecurity. With Analytic Solver, users don’t need coding skills, ‘DevOps’, ‘ModelOps’ or IT expertise – they use a Deployment Wizard to turn their Excel models into a form easily usable in Microsoft Teams, Power BI, Power Apps, Power Automate, or any application that can consume JSON or OData. The combination is a complete “decision intelligence suite” that supports business rules, forecasting, machine learning, optimization and simulation methods, from small models to large, multi-stage analytics workflows. Decision Intelligence Results in Months, not YearsĪnalytic Solver works with RASON, Frontline’s Azure-hosted platform, to empower users to ‘publish’ and manage analytic models as RESTful decision services. “With Analytic Solver, business analysts have powerful optimization, risk analysis and machine learning capabilities - and they can ‘move beyond Excel’ to gain cloud-based data access, model management and governance, without losing the advantages of Excel”, said Daniel Fylstra, Frontline’s President and CEO.
INCLINE VILLAGE, NV – Decem– Frontline Systems is shipping Analytic Solver® V2022, a new version of its advanced analytics toolset for Excel (Web, Windows and Macintosh), that enables business analysts to easily build models using business rules, machine learning, mathematical optimization and Monte Carlo simulation, and easily deploy those models in cloud-based applications.Īnalytic Solver is upward compatible from the Solver in Excel, which Frontline originally developed for Microsoft, and is able to solve virtually any type or size of optimization model – using methods from linear programming to genetic algorithms and stochastic optimization, ranging from a few to millions of inter-related decisions in a single model. Tool enables business analysts to create analytics-powered decision services, “point and click” without coding, using optimization, Monte Carlo simulation, data mining and machine learning, rules and decision tables works in Excel for the Web, Windows and Macintosh and with Microsoft Teams.