Frontline Systems Releases Analytic Solver® V2023 with Patent-Pending Risk Analysis for Machine Learning Models

Analytic Solver V2023

With a patent utility now on file to protect invention rights, Analytic Solver customers are the primary to learn from these revolutionary strategies.

INCLINE VILLAGE, Nev. (PRWEB)
September 19, 2022
Frontline Systems is delivery Analytic Solver® V2023, a brand new model of its superior analytics toolset for Excel (Web, Windows, and Macintosh), that permits enterprise analysts to simply construct fashions utilizing enterprise guidelines, machine studying, mathematical optimization, and Monte Carlo simulation, and simply deploy these fashions in cloud-based functions.
Analytic Solver shouldn’t be new – it’s a market-leading analytics device upward suitable from the Solver in Excel, which Frontline initially developed for Microsoft. But now it’s the primary and solely device with totally automated strategies for threat evaluation of beforehand skilled and validated machine studying (ML) fashions.
As an “Excel Solver improve”, Analytic Solver can deal with just about any kind or measurement of optimization downside, starting from just a few to thousands and thousands of inter-related choices in a single mannequin. And for years, Analytic Solver has provided highly effective options for threat evaluation utilizing Monte Carlo simulation, and highly effective options for coaching, validating, and deploying predictive fashions utilizing machine studying.
Now, Analytic Solver V2023 consists of an revolutionary functionality for threat evaluation of machine studying fashions that leverages a number of capabilities of the software program. Risk evaluation adjustments the main focus from how precisely a ML mannequin will predict a single new case, to the way it will carry out in mixture over 1000’s or thousands and thousands of recent instances, what the enterprise penalties shall be, and the (quantified) threat that this shall be completely different than anticipated from the ML mannequin’s coaching and validation.
“With a patent utility now on file to protect invention rights, Analytic Solver customers are the primary to learn from these revolutionary strategies”, mentioned Daniel Fylstra, Frontline’s President and CEO. Frontline Systems is concurrently releasing new variations of RASON®, its cloud platform for analytics, and Solver SDK®, its toolkit for software program builders, with help for the identical revolutionary strategies.
How and Why Machine Learning has Lacked Risk Analysis
For a decade, knowledge science and machine studying (DSML) instruments – together with Analytic Solver – have provided amenities for ‘coaching’ a mannequin on one set of information, ‘validating’ its efficiency on one other set of information, and ‘testing’ it versus different ML fashions on a 3rd set of information. But this isn’t threat evaluation: based mostly on identified knowledge, it doesn’t assess the danger that the ML mannequin will carry out in a different way on new knowledge when put into manufacturing use. While it’s frequent to evaluate a ML mannequin’s efficiency in use, and transfer to re-train the mannequin if its efficiency is unexpectedly poor, by that point these dangers have occurred, usually with antagonistic monetary penalties. Quantification of such dangers “forward of time” has been lacking in apply.
There are many causes for this state of affairs: Data scientists with experience in ML strategies usually aren’t skilled in threat evaluation; they consider “options” and even predicted output values as knowledge, not as “random variables” with sampled situations. Even if identified, typical threat evaluation strategies are costly and time-consuming to use to machine studying: ML knowledge units embody many (generally lots of) of options, with restricted “provenance” of the info’s origins. There are lots of of classical chance distributions that may very well be ‘candidates’ to suit every function. Only a number of the options are usually discovered, after ML mannequin coaching, to have predictive worth; many are discovered to be correlated with different options and therefore ‘redundant’. And in typical initiatives, an awesome many ML fashions are constructed.
How Analytic Solver Performs Automated Risk Analysis
Unlike most different DSML software program, Analytic Solver consists of highly effective algorithms for threat evaluation in the identical bundle: Probability distribution becoming, correlation becoming, stratified pattern era, and Monte Carlo evaluation. But asking enterprise analysts – not to mention knowledge scientists – to “rapidly grasp threat evaluation” is asking an excessive amount of. So Frontline Systems has invented methods to automate your entire threat evaluation course of. Using the brand new functionality is so simple as checking one additional field in a dialog, with some additional “level and click on” choices for evaluation and reporting – and the danger evaluation usually provides simply seconds to a minute to the prevailing course of of coaching, validating, and testing a ML mannequin.
Behind the scenes, for every function, Analytic Solver exams a whole household of chance distributions – drawing on its first-mover help for the brand new Metalog household of distributions, created by Dr. Tom Keelin; optimizes all of the parameters of every distribution; detects and fashions correlations amongst options, utilizing rank order and copula strategies; performs artificial knowledge era, utilizing Monte Carlo strategies for stratified sampling and correlation; computes the ML mannequin’s predictions, in addition to user-specified monetary penalties, for every simulated case; and importantly, assesses and quantifies the variations in efficiency of the ML mannequin on this simulated knowledge versus the coaching, validation and take a look at knowledge.
The person sees outcomes of the danger evaluation in automatically-generated charts, statistics, and threat measures – drawing from the Monte Carlo simulation options of Analytic Solver, confirmed in use over a few years.
Synthetic Data Generation as a Side Benefit
Synthetic Data Generation (SDG) has develop into topical in machine studying lately, with numerous firms based simply to provide software program and providers round this know-how. SDG is used when there isn’t sufficient unique knowledge, or when use of the unique knowledge is restricted by legislation or regulation. But till now (in a patent and literature search), SDG has merely been used to raised practice ML fashions.
Analytic Solver V2023 features a highly effective, general-purpose, straightforward to make use of Synthetic Data Generation facility, accessible from the Excel Ribbon. Unlike some special-purpose SDG choices, this facility can precisely mannequin the conduct of almost any mixture of options with steady values. But Analytic Solver additionally makes use of artificial knowledge in a completely new manner, to research the danger {that a} ML mannequin will yield surprising outcomes “massive sufficient to matter” when deployed for manufacturing use.
Works with Already-Available ‘Augmented Machine Learning’
Analytic Solver’s V2021.5 launch featured “augmented machine studying” options discovered solely in different subtle machine studying instruments. The person merely provides knowledge, and selects a menu possibility “Find Best Model”: Analytic Solver will robotically take a look at and match parameters for a number of sorts of machine studying fashions – classification and regression bushes, neural networks, linear and logistic regression, discriminant evaluation, naïve Bayes, k-nearest neighbors and extra – then validate and evaluate them in line with user-chosen standards, and ship the mannequin that most closely fits the info.
Analytic Solver V2021.5 additionally featured enhancements that allow multi-stage “knowledge science workflows” together with machine studying fashions constructed and examined in Excel, to be deployed robotically to RASON® Decision Services, Frontline Systems’ complete cloud platform for choice intelligence.
But now that it’s attainable and even straightforward, customers will need to assess the danger of a ML mannequin earlier than it’s deployed. With just a few mouse clicks, Analytic Solver V2023’s automated threat evaluation could be utilized to the mannequin delivered by “Find Best Model”. When the analyst or decision-maker is glad, with just a few extra mouse clicks, the mannequin could be deployed as a cloud service with an easy-to-use REST API.
Free Trials, Learning, and Coaching Resources
Business analysts and builders can join for free trial accounts to guage Analytic Solver at https://www.solver.com, and RASON at https://rason.com. They can use instruments to create and clear up fashions in Excel and RASON, train the REST API, check out dozens of instance fashions illustrating use of choice tables, predictive fashions and machine studying, optimization and simulation, and obtain the Analytic Solver and RASON User Guides and Reference Guides in PDF kind. For extra info please contact gross [email protected]
Frontline Systems Inc. (http://www.solver.com) is the choice to analytics complexity, serving to enterprise analysts and managers acquire insights and make higher choices for an unsure future, with out the fee, delays, and threat of ‘large vendor’ instruments. Its merchandise combine forecasting and knowledge mining for “predictive analytics,” Monte Carlo simulation for threat evaluation, typical and stochastic optimization for “prescriptive analytics,” and enterprise guidelines and Excel calculations to make the very best enterprise choices. Founded in 1987, Frontline relies in Incline Village, Nevada (775-831-0300).
Microsoft Excel and Office 365 are emblems of Microsoft Corp. Analytic Solver®, RASON®, and Solver SDK® are registered emblems of Frontline Systems Inc.

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