Before designing a circuit with GeneXproTools 4.0 you must first load the
truth tables for the learning algorithm. The data screening engine of GeneXproTools 4.0 checks the validity of all the
truth tables and is operative every time you load data sets
either for training or testing. Only the values of False and True
(case insensitive) or "0" and "1" are valid as
input. Note,
however, that GeneXproTools uses 0's and 1's internally and,
therefore, False and True are respectively converted into
"0" and "1" and shown in this format. Missing or
invalid values can be detected by the data screening engine so that
you can identify these faulty samples and correct them.
GeneXproTools 4.0 allows you to work either with databases/Excel or text
files and, for text files, accepts two different data matrix formats.
The first is the standard Samples x
Variables format where samples are in rows and variables in
columns, with the dependent variable or function output occupying the
rightmost position. In the small example below with eight samples,
OUTPUT is the function output and A, B, and C are the independent
variables:
A B C OUTPUT
0 0 0 0
0 0 1 0
0 1 0 0
0 1 1 1
1 0 0 0
1 0 1 1
1 1 0 1
1 1 1 1
And the second, is the Gene Expression Matrix format commonly used
in DNA microarrays studies where samples are in columns and
variables in rows, with the function output occupying the topmost position. For instance, in Gene Expression
Matrix format, the truth table above corresponds to:
OUTPUT 0 0 0 1 0 1 1 1
A 0 0 0 0 1 1 1 1
B 0 0 1 1 0 0 1 1
C 0 1 0 1 0 1 0 1
which is very handy for
datasets with a relatively small number of samples and thousands of
variables. Note, however, that for Excel files this format is not
supported and if your data is kept in this format in Excel, you must
copy it to a text file so that it can be loaded into GeneXproTools.
GeneXproTools uses
the Samples x
Variables format throughout and therefore all formats are automatically
converted and shown in this format.
GeneXproTools supports the standard separators (space,
tab, comma, semicolon, and pipe) and detects them automatically. The
use of labels to identify your variables is optional and
GeneXproTools also detects automatically whether they are
present or not. If you use them, however, you will be able to
generate more intelligible code where each variable is identified by
its name, by checking the Use Labels box in the Model Panel.
To Load Truth Tables for Modeling
- Click the File Menu and then choose New.
The New Run Wizard appears. You must give a name to your new run file (the default filename extension of
GeneXproTools 4.0 run files is .gep) and then choose Logic
Synthesis in the Problem Category box and the kind of source
file in the Data Source Type box.
GeneXproTools 4.0 allows you to work either with Excel/databases or text
files.
- Then go to the Training Data window by clicking the Next button.
Choose the path for the training set by browsing the Open dialog
box and choose the appropriate data matrix format. Irrespective
of the data format used,
GeneXproTools shows the loaded data in the standard Samples x
Variables format, with the function output or dependent variable
occupying the
rightmost position.
- Then go to the Testing Data window by clicking the Next button.
The use of a testing set is not common practice in Logic
Synthesis as usually the entire truth table is used to design
the logic circuit, but repeat the same steps of the previous point if you wish to use a
testing set to evaluate the predictive accuracy of your circuit.
- Click the Finish button to save your new run file.
The Save As dialog box appears and after choosing the directory where you want your new run file to be saved, the
GeneXproTools modeling environment appears.
Then you just have to click the Evolve button to design a logic
circuit as
GeneXproTools automatically chooses, from a gallery of templates, default settings that will enable you to
design one immediately.
After loading your data into
GeneXproTools, in the Data Panel you can visualize the distribution of values for each variable and also plot each independent variable against the
function output or dependent variable.
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