Classification and regression trees

Classification and regression trees is part of:

  • Pro Core statistical software

  • System configuration

    • Windows:
      • Versions: 9x/Me/NT/2000/XP/Vista/Win 7
      • Excel: 97 and later
      • Processor: 32 or 64 bits
      • Hard disk: 150 Mb
    • Mac OS X:
      • OS: OS X
      • Excel: X, 2004 and 2011
      • Hard disk: 150Mb.

Benefits

  • Easy and user-friendly
    Easy and user-friendly XLSTAT is flawlessly integrated with Microsoft Excel which is the most popular spreadsheet worldwide. This integration makes it one of the simplest available tools to work with as it utilizes the same philosophy as Microsoft Excel. The program is accessible in a dedicated XLSTAT tab. The analyses are grouped into functional menus. The dialog boxes are user-friendly and setting up an analysis is straightforward.
  • Data and results shared seamlessly
    Data and results shared seamlessly One of the greatest advantages of XLSTAT is the way you can share data and results seamlessly. As the results are stored in Microsoft Excel, anyone can access them. There is no need for the receiver to have an XLSTAT license or any additional viewer which makes your team-work easier and more affordable. In addition, results are easily integrable into other Microsoft Office software such as PowerPoint, so that you can create striking presentation in minutes.
  • Modular
    Modular XLSTAT is a modular product. XLSTAT-Pro is a core statistical module of XLSTAT which includes all the mainstream functionalities in statistics and multivariate analysis. More advanced features contained in add-on modules can be added for specific applications. This way you can adapt the software to your needs making the software more cost-efficient.
  • Didactic
    Didactic The results of XLSTAT are organized by analysis and are easy to navigate. Moreover useful information is provided along with the results to assist you in your interpretation.
  • Affordable
    Affordable XLSTAT is a complete and modular analytical solution that can suit any analytical business needs. It is very reasonably priced so that the return of your investment is almost immediate. Any XLSTAT license comes with top level support and assistance.
  • Accessible - Available in many languages
    Accessible - Available in many languages We have ensured XLSTAT is accessible to everyone by making the program available in many languages, including Chinese, English, French, German, Italian, Japanese, Polish, Portuguese and Spanish.
  • Automatable and customizable
    Automatable and customizable Most of the statistical functions available in XLSTAT can be called directly from the Visual Basic window of Microsoft Excel. They can be modified and integrated to more code to fit to the specificity of your domain. Adding tables and plots as well as modifying existing outputs becomes easy. Furthermore, XLSTAT includes some special tools on the dialog boxes to generate automatically the VBA code in order to reproduce your analysis using the VBA editor or to simply load pre-set settings. This effortless automation of routine analysis will be a huge time saver on your part.

Use of classification and regression trees

Classification and regression trees are methods that deliver models that meet both explanatory and predictive goals. Two of the strengths of this method are on the one hand the simple graphical representation by trees, and on the other hand the compact format of the natural language rules.

We distinguish the following two cases where these modeling techniques should be used:

Algorithms for classification and regression trees in XLSTAT

XLSTAT uses the CHAID, exhaustive CHAID, QUEST and C&RT (Classification and Regression Trees) algorithms.

Classification and regression trees apply to quantitative and qualitative dependent variables. In the case of a Discriminant analysis or logistic regression, only qualitative dependent variables can be used. In the case of a qualitative depending variable with only two categories, the user will be able to compare the performances of both methods by using ROC curves.

Results for classification and regression trees in XLSTAT

Among the numerous results provided, XLSTAT can display the classification table (also called confusion matrix) used to calculate the percentage of well-classified observations. The proportion of well-classified positive events is called the sensitivity. The specificity is the proportion of well-classified negative events. If you vary the threshold probability from which an event is to be considered positive, the sensitivity and specificity will also vary.

When only two classes are present in the dependent variable, the ROC (Receiver Operating Characteristics) curve may also be displayed. It is the curve of points (1-specificity, sensitivity). It can be used for comparison with other models as it displays the performance of a model. The area under the curve (or AUC) is a synthetic index calculated for ROC curves. The AUC corresponds to the probability such that a positive event has a higher probability given to it by the model than a negative event. For an ideal model, AUC=1 and for a random model, AUC = 0.5. A model is usually considered good when the AUC value is greater than 0.7. A well-discriminating model must have an AUC of between 0.87 and 0.9. A model with an AUC greater than 0.9 is excellent.

Validation for classification and regression trees

You are advised to validate the model on a validation sample wherever possible. XLSTAT has several options for generating a validation sample automatically.

Tutorials

Screenshots