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Products / Forecaster XL / Feature Set
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General
- Regression, classification types of forecasting
- Time-series forecasting
- Exceptional ease of use
- Constructive neural network algorithms
- Informative graphs and detailed reports
- Online help system
- Free technical support
- Multi-language interface
- Sample financial, marketing, real estate and scientific problems included
Analyze Your Data
- Number of inputs and records are limited only by Excel limitations
- Automatic data analysis and pre-processing
- Automatic categorical values encoding
- Automatic numeric values scaling
- Missing values handling for numeric values (removal and 4 substitution options)
- Missing values handling for categorical values (removal and 3 substitution options)
- Outliers handling (customizable outlier coefficient)
- Manual min/max values specification to anticipate bigger values in data for forecasting
- Automatic random and sequential dataset partition onto training and test sets
- Detailed Data Analysis and Preprocessing Report
Create Neural Network
- Fully automated neural network design - a special state-of-the-art constructive algorithm automatically creates and trains the most suitable neural network to solve your problem.
- Neural networks for time-series forecasting
- Unique "Next Target" mode: combination of regression and time-series forecasting
- Automatic generation of versatile stopping condition to stop network training
- Generalization loss control (10 preset levels)
- Retain and restore best network
- Manual network retrain
- Retrain network to get better results
For experienced users
- Manual stopping conditions (target error level, error improvement, correct classification rate, number of iterations)
- Real-time control on training parameters (MSE, MAE, CCR, # of iterations).
- Training Error Graph (network error by iteration)
- Training Error Table (network error and error improvement by iteration)
- Cost/Loss matrix
Perform Performance Analysis and Forecasting
- Actual vs Forecasted Graph
- Actual vs Forecasted Scatter Plot
- Input Importance Chart
- Error deviation graph
- Actual vs Forecasted Table with absolute and relative errors
- Confusion matrix
- Error distribution table
- R-squared and correlation calculation for a network
- Tolerance levels to quickly estimate overall forecasting quality
- Single-point forecasting and bulk forecasting
- Quick forecasting with already trained network
Enjoy User Interface Extras
- two convenient methods of data selection: by range and by column
- complete color customization for reports and graphs
- neural network autosave
- load/save neural network from/to Excel worksheet/workbook
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