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- #
- #
- #---- example2.lf
- #!!!! requires example1.lf to be run first !!!!
- #
- #---- This is an lf example that tests both the XOR, NXOR,
- #---- and AND functions of two binary inputs learned in
- #---- example1.lf.
- #
- #---- The trees saved into the file example1.tre are used with
- #---- the encodings from the file example1.cod.
- #---- Note that a saved set of trees must be accompanied
- #---- by its corresponding encodings if the tree is to function
- #---- properly in future trials where the trees are loaded
- #---- instead of generated.
- #
-
- #---- specify tree statements
- tree
-
- #---- test on trees generated in example1.lf
- load tree from "example1.tre"
-
- #---- specify function statements
- function
-
- #---- domain dimension must be the first statement, followed
- #---- by the codomain dimension
- domain dimension = 2
-
- #---- we are testing on 3 functions at once, XOR, NXOR, and AND
- #---- which means there are 3 codimensions
- codomain dimension = 3
-
- #---- load encoding generated in example1.lf for use with example1.tre
- load coding from "example1.cod"
-
- #---- there are no rows in our training set
- #---- note that there is NO "training set =" statement
- training set size = 0
-
- #---- we will test on the following 4 vectors
- test set size = 4
- test set =
- # A B A xor B A nxor B A and B
- 1 1 0 1 1
- 1 0 1 0 0
- 0 1 1 0 0
- 0 0 0 1 0
-
- #---- The following output file should be generated:
- #---- The first line indicates how many codomains there are.
- #---- The next four lines represent each of the four lines in the test set.
- #---- Each value is followed by its corresponding quantization number
- #---- in the prescribed encoding scheme. Each codomain is followed
- #---- by the corresponding result from the ALN's, along with its quantization
- #---- number. Remember, it's not the calculated value that is as important
- #---- as the calculated quantization level. You can get more accurate values
- #---- by tightening up the encoding: increasing the number of quantization
- #---- levels.
-
- #---- After the results is the error histogram, which counts for each
- #---- of the codomains the number of times the result quantization
- #---- level differed from the actual quantization level by n. In this example,
- #---- the ALN's executed the test set perfectly, so there are 4 counts for
- #---- errors of n = 0 in each of the 3 codomains.
-
-
- # A B A xor B A xor B result A nxor B A nxor B result A and B A and B result
-
- #3
- #1.000000 1 1.000000 1 0.000000 0 0.000000 0 1.000000 1 1.000000 1 1.000000 1 1.000000 1
- #1.000000 1 0.000000 0 1.000000 1 1.000000 1 0.000000 0 0.000000 0 0.000000 0 0.000000 0
- #0.000000 0 1.000000 1 1.000000 1 1.000000 1 0.000000 0 0.000000 0 0.000000 0 0.000000 0
- #0.000000 0 0.000000 0 0.000000 0 0.000000 0 1.000000 1 1.000000 1 0.000000 0 0.000000 0
- #
- #ERROR HISTOGRAM
- #0 errors 4 4 4
- #1 errors 0 0 0
- #2 errors 0 0 0
- #3 errors 0 0 0
- #4 errors 0 0 0
- #5 errors 0 0 0
- #6 errors 0 0 0
- #7 errors 0 0 0
- #8 errors 0 0 0
- #9+ errors 0 0 0
-