Icon of program: Alyuda Forecaster XL

Alyuda Forecaster XL for Windows

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Editors’ Review

Download.com staff
Alyuda Forecaster XL is an MS Excel add-in leveraging neural networks for automated forecasting and data mining. It excels at regression, time-series, and classification tasks.

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  • Pros

    • Automated neural network architecture selection and training.
    • Unique combination forecasting mode.
    • Comprehensive performance and data reports.
    • Automatic outlier and missing value handling.
    • Manual expert control options available.

  • Cons

    • Add-in functionality requires MS Excel installation.
Icon of program: Alyuda Forecaster XL

Alyuda Forecaster XL for Windows

Download now

Used Alyuda Forecaster XL for Windows?

Explore More

Full Specifications

GENERAL
Release
Latest update
Version
2.0
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows 95
  • Windows 10
  • Windows XP
  • Windows 98
  • Windows ME
  • Windows 2000
Additional Requirements
Windows 95/98/Me/2000/XP, Microsoft Excel 2000
POPULARITY
Total Downloads
3,589
Downloads Last Week
16
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Developer’s Description

By Alyuda Research
Perform forecasting and data mining using neural networks MS Excel add-in.
Alyuda Forecaster XL is a forecasting add-in for MS Excel based on neural networks. It features a breakthrough constructive algorithm with complete automation of neural network architecture selection and network training. It is well suited for regression forecasting, time-series forecasting and classification. Forecaster XL also offers unique forecasting mode: combination of time-series and standard regression forecasting. With this mode you can forecast next value of your output column without corresponding values for input columns for the next period.

Performance report offers actual vs. forecasted graph, scatter plot, confusion matrix, error distribution table and input column importance chart. Data report provides data anomalies visualization. Outliers and missing values can be automatically removed or substituted. Neural network experts can switch to manual determination of stop training conditions and data partition.

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