Add dataset to test and add hyperparameters to sample

This commit is contained in:
2023-02-28 00:43:37 +01:00
parent 0b63d9ace0
commit 90428218c2
2 changed files with 487 additions and 16 deletions

View File

@@ -1,31 +1,76 @@
#include <iostream>
#include <vector>
#include <iomanip>
#include <getopt.h>
#include "../CPPFImdlp.h"
#include "../tests/ArffFiles.h"
using namespace std;
using namespace mdlp;
/* print a description of all supported options */
void usage(const char* path)
{
/* take only the last portion of the path */
const char* basename = strrchr(path, '/');
basename = basename ? basename + 1 : path;
int main(int argc, char** argv)
cout << "usage: " << basename << "[OPTION]" << endl;
cout << " -h, --help\t\t Print this help and exit." << endl;
cout << " -f, --file[=FILENAME]\t {mfeat-factors, glass, iris, letter, kdd_JapaneseVowels, liver-disorders, test}." << endl;
cout << " -m, --max_depth=INT\t max_depth pased to discretizer. Default = MAX_INT" << endl;
cout << " -n, --min_length=INT\t interval min_length pased to discretizer. Default = 3" << endl;
}
tuple<string, int, int> parse_arguments(int argc, char** argv)
{
string file_name;
int max_depth = numeric_limits<int>::max();
int min_length = 3;
static struct option long_options[] = {
{ "help", no_argument, 0, 'h' },
{ "file", required_argument, 0, 'f' },
{ "max_depth", required_argument, 0, 'm' },
{ "min_length", required_argument, 0, 'n' },
{ 0, 0, 0, 0 }
};
while (1) {
auto c = getopt_long(argc, argv, "hf:m:n:", long_options, 0);
if (c == -1)
break;
switch (c) {
case 'h':
usage(argv[0]);
exit(0);
case 'f':
file_name = optarg;
break;
case 'm':
max_depth = atoi(optarg);
break;
case 'n':
min_length = atoi(optarg);
break;
case '?':
usage(argv[0]);
exit(1);
default:
abort();
}
}
if (file_name.empty()) {
usage(argv[0]);
exit(1);
}
return make_tuple(file_name, max_depth, min_length);
}
void process_file(string file_name, bool class_last, int max_depth, int min_length)
{
ArffFiles file;
string path = "../../tests/datasets/";
map<string, bool> datasets = {
{"mfeat-factors", true},
{"iris", true},
{"letter", true},
{"glass", true},
{"kdd_JapaneseVowels", false},
{"test", true}
};
if (argc != 2 || datasets.find(argv[1]) == datasets.end()) {
cout << "Usage: " << argv[0] << " {mfeat-factors, glass, iris, letter, kdd_JapaneseVowels, test}" << endl;
return 1;
}
file.load(path + argv[1] + ".arff", datasets[argv[1]]);
file.load(path + file_name + ".arff", class_last);
auto attributes = file.getAttributes();
int items = file.getSize();
cout << "Number of lines: " << items << endl;
@@ -44,7 +89,7 @@ int main(int argc, char** argv)
}
cout << y[i] << endl;
}
mdlp::CPPFImdlp test = mdlp::CPPFImdlp();
mdlp::CPPFImdlp test = mdlp::CPPFImdlp(min_length, max_depth);
auto total = 0;
for (auto i = 0; i < attributes.size(); i++) {
auto min_max = minmax_element(X[i].begin(), X[i].end());
@@ -57,6 +102,33 @@ int main(int argc, char** argv)
}
total += test.getCutPoints().size();
}
cout << "Total cut points: " << total << endl;
cout << "Total cut points ...: " << total << endl;
cout << "Total feature states: " << total + attributes.size() << endl;
}
int main(int argc, char** argv)
{
map<string, bool> datasets = {
{"mfeat-factors", true},
{"iris", true},
{"letter", true},
{"glass", true},
{"kdd_JapaneseVowels", false},
{"liver-disorders", true},
{"test", true}
};
string file_name;
int max_depth, min_length;
tie(file_name, max_depth, min_length) = parse_arguments(argc, argv);
if (datasets.find(file_name) == datasets.end()) {
cout << "Invalid file name: " << file_name << endl;
usage(argv[0]);
exit(1);
}
process_file(file_name, datasets[file_name], max_depth, min_length);
cout << "File name: " << file_name << endl;
cout << "Max depth: " << max_depth << endl;
cout << "Min length: " << min_length << endl;
return 0;
}

View File

@@ -0,0 +1,399 @@
% 1. Title: BUPA liver disorders
%
% 2. Source information:
% -- Creators: BUPA Medical Research Ltd.
% -- Donor: Richard S. Forsyth
% 8 Grosvenor Avenue
% Mapperley Park
% Nottingham NG3 5DX
% 0602-621676
% -- Date: 5/15/1990
%
% 3. Past usage:
% -- None known other than what is shown in the PC/BEAGLE User's Guide
% (written by Richard S. Forsyth).
%
% 4. Relevant information:
% -- The first 5 variables are all blood tests which are thought
% to be sensitive to liver disorders that might arise from
% excessive alcohol consumption. Each line in the bupa.data file
% constitutes the record of a single male individual.
% -- It appears that drinks>5 is some sort of a selector on this database.
% See the PC/BEAGLE User's Guide for more information.
%
% 5. Number of instances: 345
%
% 6. Number of attributes: 7 overall
%
% 7. Attribute information:
% 1. mcv mean corpuscular volume
% 2. alkphos alkaline phosphotase
% 3. sgpt alamine aminotransferase
% 4. sgot aspartate aminotransferase
% 5. gammagt gamma-glutamyl transpeptidase
% 6. drinks number of half-pint equivalents of alcoholic beverages
% drunk per day
% 7. selector field used to split data into two sets
%
% 8. Missing values: none%
% Information about the dataset
% CLASSTYPE: nominal
% CLASSINDEX: last
%
@relation liver-disorders
@attribute mcv INTEGER
@attribute alkphos INTEGER
@attribute sgpt INTEGER
@attribute sgot INTEGER
@attribute gammagt INTEGER
@attribute drinks REAL
@attribute selector {1,2}
@data
85,92,45,27,31,0.0,1
85,64,59,32,23,0.0,2
86,54,33,16,54,0.0,2
91,78,34,24,36,0.0,2
87,70,12,28,10,0.0,2
98,55,13,17,17,0.0,2
88,62,20,17,9,0.5,1
88,67,21,11,11,0.5,1
92,54,22,20,7,0.5,1
90,60,25,19,5,0.5,1
89,52,13,24,15,0.5,1
82,62,17,17,15,0.5,1
90,64,61,32,13,0.5,1
86,77,25,19,18,0.5,1
96,67,29,20,11,0.5,1
91,78,20,31,18,0.5,1
89,67,23,16,10,0.5,1
89,79,17,17,16,0.5,1
91,107,20,20,56,0.5,1
94,116,11,33,11,0.5,1
92,59,35,13,19,0.5,1
93,23,35,20,20,0.5,1
90,60,23,27,5,0.5,1
96,68,18,19,19,0.5,1
84,80,47,33,97,0.5,1
92,70,24,13,26,0.5,1
90,47,28,15,18,0.5,1
88,66,20,21,10,0.5,1
91,102,17,13,19,0.5,1
87,41,31,19,16,0.5,1
86,79,28,16,17,0.5,1
91,57,31,23,42,0.5,1
93,77,32,18,29,0.5,1
88,96,28,21,40,0.5,1
94,65,22,18,11,0.5,1
91,72,155,68,82,0.5,2
85,54,47,33,22,0.5,2
79,39,14,19,9,0.5,2
85,85,25,26,30,0.5,2
89,63,24,20,38,0.5,2
84,92,68,37,44,0.5,2
89,68,26,39,42,0.5,2
89,101,18,25,13,0.5,2
86,84,18,14,16,0.5,2
85,65,25,14,18,0.5,2
88,61,19,21,13,0.5,2
92,56,14,16,10,0.5,2
95,50,29,25,50,0.5,2
91,75,24,22,11,0.5,2
83,40,29,25,38,0.5,2
89,74,19,23,16,0.5,2
85,64,24,22,11,0.5,2
92,57,64,36,90,0.5,2
94,48,11,23,43,0.5,2
87,52,21,19,30,0.5,2
85,65,23,29,15,0.5,2
84,82,21,21,19,0.5,2
88,49,20,22,19,0.5,2
96,67,26,26,36,0.5,2
90,63,24,24,24,0.5,2
90,45,33,34,27,0.5,2
90,72,14,15,18,0.5,2
91,55,4,8,13,0.5,2
91,52,15,22,11,0.5,2
87,71,32,19,27,1.0,1
89,77,26,20,19,1.0,1
89,67,5,17,14,1.0,2
85,51,26,24,23,1.0,2
103,75,19,30,13,1.0,2
90,63,16,21,14,1.0,2
90,63,29,23,57,2.0,1
90,67,35,19,35,2.0,1
87,66,27,22,9,2.0,1
90,73,34,21,22,2.0,1
86,54,20,21,16,2.0,1
90,80,19,14,42,2.0,1
87,90,43,28,156,2.0,2
96,72,28,19,30,2.0,2
91,55,9,25,16,2.0,2
95,78,27,25,30,2.0,2
92,101,34,30,64,2.0,2
89,51,41,22,48,2.0,2
91,99,42,33,16,2.0,2
94,58,21,18,26,2.0,2
92,60,30,27,297,2.0,2
94,58,21,18,26,2.0,2
88,47,33,26,29,2.0,2
92,65,17,25,9,2.0,2
92,79,22,20,11,3.0,1
84,83,20,25,7,3.0,1
88,68,27,21,26,3.0,1
86,48,20,20,6,3.0,1
99,69,45,32,30,3.0,1
88,66,23,12,15,3.0,1
89,62,42,30,20,3.0,1
90,51,23,17,27,3.0,1
81,61,32,37,53,3.0,2
89,89,23,18,104,3.0,2
89,65,26,18,36,3.0,2
92,75,26,26,24,3.0,2
85,59,25,20,25,3.0,2
92,61,18,13,81,3.0,2
89,63,22,27,10,4.0,1
90,84,18,23,13,4.0,1
88,95,25,19,14,4.0,1
89,35,27,29,17,4.0,1
91,80,37,23,27,4.0,1
91,109,33,15,18,4.0,1
91,65,17,5,7,4.0,1
88,107,29,20,50,4.0,2
87,76,22,55,9,4.0,2
87,86,28,23,21,4.0,2
87,42,26,23,17,4.0,2
88,80,24,25,17,4.0,2
90,96,34,49,169,4.0,2
86,67,11,15,8,4.0,2
92,40,19,20,21,4.0,2
85,60,17,21,14,4.0,2
89,90,15,17,25,4.0,2
91,57,15,16,16,4.0,2
96,55,48,39,42,4.0,2
79,101,17,27,23,4.0,2
90,134,14,20,14,4.0,2
89,76,14,21,24,4.0,2
88,93,29,27,31,4.0,2
90,67,10,16,16,4.0,2
92,73,24,21,48,4.0,2
91,55,28,28,82,4.0,2
83,45,19,21,13,4.0,2
90,74,19,14,22,4.0,2
92,66,21,16,33,5.0,1
93,63,26,18,18,5.0,1
86,78,47,39,107,5.0,2
97,44,113,45,150,5.0,2
87,59,15,19,12,5.0,2
86,44,21,11,15,5.0,2
87,64,16,20,24,5.0,2
92,57,21,23,22,5.0,2
90,70,25,23,112,5.0,2
99,59,17,19,11,5.0,2
92,80,10,26,20,6.0,1
95,60,26,22,28,6.0,1
91,63,25,26,15,6.0,1
92,62,37,21,36,6.0,1
95,50,13,14,15,6.0,1
90,76,37,19,50,6.0,1
96,70,70,26,36,6.0,1
95,62,64,42,76,6.0,1
92,62,20,23,20,6.0,1
91,63,25,26,15,6.0,1
82,56,67,38,92,6.0,2
92,82,27,24,37,6.0,2
90,63,12,26,21,6.0,2
88,37,9,15,16,6.0,2
100,60,29,23,76,6.0,2
98,43,35,23,69,6.0,2
91,74,87,50,67,6.0,2
92,87,57,25,44,6.0,2
93,99,36,34,48,6.0,2
90,72,17,19,19,6.0,2
97,93,21,20,68,6.0,2
93,50,18,25,17,6.0,2
90,57,20,26,33,6.0,2
92,76,31,28,41,6.0,2
88,55,19,17,14,6.0,2
89,63,24,29,29,6.0,2
92,79,70,32,84,7.0,1
92,93,58,35,120,7.0,1
93,84,58,47,62,7.0,2
97,71,29,22,52,8.0,1
84,99,33,19,26,8.0,1
96,44,42,23,73,8.0,1
90,62,22,21,21,8.0,1
92,94,18,17,6,8.0,1
90,67,77,39,114,8.0,1
97,71,29,22,52,8.0,1
91,69,25,25,66,8.0,2
93,59,17,20,14,8.0,2
92,95,85,48,200,8.0,2
90,50,26,22,53,8.0,2
91,62,59,47,60,8.0,2
92,93,22,28,123,9.0,1
92,77,86,41,31,10.0,1
86,66,22,24,26,10.0,2
98,57,31,34,73,10.0,2
95,80,50,64,55,10.0,2
92,108,53,33,94,12.0,2
97,92,22,28,49,12.0,2
93,77,39,37,108,16.0,1
94,83,81,34,201,20.0,1
87,75,25,21,14,0.0,1
88,56,23,18,12,0.0,1
84,97,41,20,32,0.0,2
94,91,27,20,15,0.5,1
97,62,17,13,5,0.5,1
92,85,25,20,12,0.5,1
82,48,27,15,12,0.5,1
88,74,31,25,15,0.5,1
95,77,30,14,21,0.5,1
88,94,26,18,8,0.5,1
91,70,19,19,22,0.5,1
83,54,27,15,12,0.5,1
91,105,40,26,56,0.5,1
86,79,37,28,14,0.5,1
91,96,35,22,135,0.5,1
89,82,23,14,35,0.5,1
90,73,24,23,11,0.5,1
90,87,19,25,19,0.5,1
89,82,33,32,18,0.5,1
85,79,17,8,9,0.5,1
85,119,30,26,17,0.5,1
78,69,24,18,31,0.5,1
88,107,34,21,27,0.5,1
89,115,17,27,7,0.5,1
92,67,23,15,12,0.5,1
89,101,27,34,14,0.5,1
91,84,11,12,10,0.5,1
94,101,41,20,53,0.5,2
88,46,29,22,18,0.5,2
88,122,35,29,42,0.5,2
84,88,28,25,35,0.5,2
90,79,18,15,24,0.5,2
87,69,22,26,11,0.5,2
65,63,19,20,14,0.5,2
90,64,12,17,14,0.5,2
85,58,18,24,16,0.5,2
88,81,41,27,36,0.5,2
86,78,52,29,62,0.5,2
82,74,38,28,48,0.5,2
86,58,36,27,59,0.5,2
94,56,30,18,27,0.5,2
87,57,30,30,22,0.5,2
98,74,148,75,159,0.5,2
94,75,20,25,38,0.5,2
83,68,17,20,71,0.5,2
93,56,25,21,33,0.5,2
101,65,18,21,22,0.5,2
92,65,25,20,31,0.5,2
92,58,14,16,13,0.5,2
86,58,16,23,23,0.5,2
85,62,15,13,22,0.5,2
86,57,13,20,13,0.5,2
86,54,26,30,13,0.5,2
81,41,33,27,34,1.0,1
91,67,32,26,13,1.0,1
91,80,21,19,14,1.0,1
92,60,23,15,19,1.0,1
91,60,32,14,8,1.0,1
93,65,28,22,10,1.0,1
90,63,45,24,85,1.0,2
87,92,21,22,37,1.0,2
83,78,31,19,115,1.0,2
95,62,24,23,14,1.0,2
93,59,41,30,48,1.0,2
84,82,43,32,38,2.0,1
87,71,33,20,22,2.0,1
86,44,24,15,18,2.0,1
86,66,28,24,21,2.0,1
88,58,31,17,17,2.0,1
90,61,28,29,31,2.0,1
88,69,70,24,64,2.0,1
93,87,18,17,26,2.0,1
98,58,33,21,28,2.0,1
91,44,18,18,23,2.0,2
87,75,37,19,70,2.0,2
94,91,30,26,25,2.0,2
88,85,14,15,10,2.0,2
89,109,26,25,27,2.0,2
87,59,37,27,34,2.0,2
93,58,20,23,18,2.0,2
88,57,9,15,16,2.0,2
94,65,38,27,17,3.0,1
91,71,12,22,11,3.0,1
90,55,20,20,16,3.0,1
91,64,21,17,26,3.0,2
88,47,35,26,33,3.0,2
82,72,31,20,84,3.0,2
85,58,83,49,51,3.0,2
91,54,25,22,35,4.0,1
98,50,27,25,53,4.0,2
86,62,29,21,26,4.0,2
89,48,32,22,14,4.0,2
82,68,20,22,9,4.0,2
83,70,17,19,23,4.0,2
96,70,21,26,21,4.0,2
94,117,77,56,52,4.0,2
93,45,11,14,21,4.0,2
93,49,27,21,29,4.0,2
84,73,46,32,39,4.0,2
91,63,17,17,46,4.0,2
90,57,31,18,37,4.0,2
87,45,19,13,16,4.0,2
91,68,14,20,19,4.0,2
86,55,29,35,108,4.0,2
91,86,52,47,52,4.0,2
88,46,15,33,55,4.0,2
85,52,22,23,34,4.0,2
89,72,33,27,55,4.0,2
95,59,23,18,19,4.0,2
94,43,154,82,121,4.0,2
96,56,38,26,23,5.0,2
90,52,10,17,12,5.0,2
94,45,20,16,12,5.0,2
99,42,14,21,49,5.0,2
93,102,47,23,37,5.0,2
94,71,25,26,31,5.0,2
92,73,33,34,115,5.0,2
87,54,41,29,23,6.0,1
92,67,15,14,14,6.0,1
98,101,31,26,32,6.0,1
92,53,51,33,92,6.0,1
97,94,43,43,82,6.0,1
93,43,11,16,54,6.0,1
93,68,24,18,19,6.0,1
95,36,38,19,15,6.0,1
99,86,58,42,203,6.0,1
98,66,103,57,114,6.0,1
92,80,10,26,20,6.0,1
96,74,27,25,43,6.0,2
95,93,21,27,47,6.0,2
86,109,16,22,28,6.0,2
91,46,30,24,39,7.0,2
102,82,34,78,203,7.0,2
85,50,12,18,14,7.0,2
91,57,33,23,12,8.0,1
91,52,76,32,24,8.0,1
93,70,46,30,33,8.0,1
87,55,36,19,25,8.0,1
98,123,28,24,31,8.0,1
82,55,18,23,44,8.0,2
95,73,20,25,225,8.0,2
97,80,17,20,53,8.0,2
100,83,25,24,28,8.0,2
88,91,56,35,126,9.0,2
91,138,45,21,48,10.0,1
92,41,37,22,37,10.0,1
86,123,20,25,23,10.0,2
91,93,35,34,37,10.0,2
87,87,15,23,11,10.0,2
87,56,52,43,55,10.0,2
99,75,26,24,41,12.0,1
96,69,53,43,203,12.0,2
98,77,55,35,89,15.0,1
91,68,27,26,14,16.0,1
98,99,57,45,65,20.0,1