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6.5 The Analysis Menu

The Analysis menu is where we do our serious work in HelixTree. Up to this point in this documentation we have been acquiring, converting and manipulating data to get it ready for recursive partitioning analysis.

Figure 6.22:

The Analysis menu showing the various tools.

6.5.1 Interactive Tree Analysis

The menu choice Analysis->Interactive Tree Analysis opens up the tree view. This is covered in depth in Chapter 7, Interactive Tree Analysis.

6.5.2 Create a Multiple-Tree Model

This menu choice will create a forest of random trees for analysis. This is covered in depth in Chapter 9, Random Tree Generation.

6.5.3 Apply a Tree Model

This menu choice allows you to make predictions using a tree model. Using tree models for predictions is demonstrated in Chapter 8, Prediction Recipes.

6.5.4 Regression Analysis

This menu item opens an options dialog for Regression Analysis. For details of this analysis, see Chapter 24, Regression Analysis.

6.5.5 Plot Numeric Columns

This menu item will open a plot where you can view the active real or integer type data columns against the row labels. If the spreadsheet does not have row labels, the row numbers will be used for the x-axis. If a real or integer type spreadsheet column is set to dependent, that plot will be initially selected to be visible. Otherwise the plot from the first active data column will be initially selected to be visible. A drop down menu on the right side allows you to select the plot for a different column.

A second drop down menu at the lower right corner allows you to select whether to view the actual data values of the selected column v or the negative logarithm base 10 of the values of that column -log ₁₀v. When the plot is first created, this will default to -log ₁₀v for every column that HelixTree determines is probably a p-value output, and to the actual values for the other columns.

NOTE: To quickly plot data for just a single numeric column, click on that column’s header button and select Plot This Column (6.2.5).

For a detailed description of the plot features, see Chapter 16, P-Value and Spreadsheet Plots.

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