View multiple validation measures and display lift charts, ROC curves, CaRT trees, Scree plots and more. Explore data visually, use feature selection, clustering and principal components, transform data with binning, re-scaling and missing value handling, partition into training and validation sets, then apply ARIMA and exponential smoothing, linear and logistic regression, k-nearest neighbors, naïve Bayes, classification and regression trees (CaRT), neural networks, and ensembles of multiple algorithms. You can use data in Excel workbooks, PowerPivot datasets, SQL databases, and “big datasets” using our built-in connection to Apache Spark clusters. For a free option, see our XLMiner Analysis Toolpak add-in. Please note that Analytic Solver Data Mining is our “full-power version” designed for large-scale industrial problems – you’ll need either a free trial license or a paid license from Frontline Systems in order to use it.
You can use Analytic Solver to detect seasonal patterns in demand for better forecasts, predict which subscription customers are likely to "churn", choose whether to approve mortgage applications, check transactions for possible fraud, display products of greatest interest to online shoppers, trigger equipment maintenance ahead of predicted failures, or measure positive or negative sentiment in social media text – and that’s only the beginning. One paid license enables you to use all features of both add-ins – so be sure to get them both! You can use them in Excel for Windows, Excel for Macintosh, and Excel Online through a browser. This add-in can be used alone, but it’s designed to work with Frontline’s Analytic Solver add-in, offering powerful Monte Carlo simulation and conventional and stochastic optimization.
With the Analytic Solver® Data Mining add-in, created by Frontline Systems, developers of Solver in Microsoft Excel, you can create and train time series forecasting, data mining and text mining models in your Excel workbook, using a wide array of statistical and machine learning methods.
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