353 lines
12 KiB
C++
353 lines
12 KiB
C++
/*
|
|
* This rice classification example uses data from the UC Irvine Machine Learning repository.
|
|
* The data for this example can be found at:
|
|
* https://archive.ics.uci.edu/dataset/545/rice+cammeo+and+osmancik
|
|
*
|
|
* Copyright (C) 2024 Brett Terpstra
|
|
*
|
|
* This program is free software: you can redistribute it and/or modify
|
|
* it under the terms of the GNU General Public License as published by
|
|
* the Free Software Foundation, either version 3 of the License, or
|
|
* (at your option) any later version.
|
|
*
|
|
* This program is distributed in the hope that it will be useful,
|
|
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
* GNU General Public License for more details.
|
|
*
|
|
* You should have received a copy of the GNU General Public License
|
|
* along with this program. If not, see <https://www.gnu.org/licenses/>.
|
|
*/
|
|
#include <blt/gp/program.h>
|
|
#include <blt/profiling/profiler_v2.h>
|
|
#include <blt/gp/tree.h>
|
|
#include <blt/std/logging.h>
|
|
#include <blt/format/format.h>
|
|
#include <blt/parse/argparse.h>
|
|
#include <iostream>
|
|
#include "operations_common.h"
|
|
#include "blt/fs/loader.h"
|
|
|
|
static const auto SEED_FUNC = [] { return std::random_device()(); };
|
|
|
|
enum class rice_type_t
|
|
{
|
|
Cammeo,
|
|
Osmancik
|
|
};
|
|
|
|
struct rice_record
|
|
{
|
|
float area;
|
|
float perimeter;
|
|
float major_axis_length;
|
|
float minor_axis_length;
|
|
float eccentricity;
|
|
float convex_area;
|
|
float extent;
|
|
rice_type_t type;
|
|
};
|
|
|
|
std::vector<rice_record> training_cases;
|
|
std::vector<rice_record> testing_cases;
|
|
|
|
blt::gp::prog_config_t config = blt::gp::prog_config_t()
|
|
.set_initial_min_tree_size(2)
|
|
.set_initial_max_tree_size(6)
|
|
.set_elite_count(2)
|
|
.set_crossover_chance(0.9)
|
|
.set_mutation_chance(0.1)
|
|
.set_reproduction_chance(0)
|
|
.set_max_generations(50)
|
|
.set_pop_size(5000)
|
|
.set_thread_count(0);
|
|
|
|
blt::gp::gp_program program{SEED_FUNC, config};
|
|
|
|
auto lit = blt::gp::operation_t([]() {
|
|
return program.get_random().get_float(-32000.0f, 32000.0f);
|
|
}, "lit").set_ephemeral();
|
|
|
|
blt::gp::operation_t op_area([](const rice_record& rice_data) {
|
|
return rice_data.area;
|
|
}, "area");
|
|
|
|
blt::gp::operation_t op_perimeter([](const rice_record& rice_data) {
|
|
return rice_data.perimeter;
|
|
}, "perimeter");
|
|
|
|
blt::gp::operation_t op_major_axis_length([](const rice_record& rice_data) {
|
|
return rice_data.major_axis_length;
|
|
}, "major_axis_length");
|
|
|
|
blt::gp::operation_t op_minor_axis_length([](const rice_record& rice_data) {
|
|
return rice_data.minor_axis_length;
|
|
}, "minor_axis_length");
|
|
|
|
blt::gp::operation_t op_eccentricity([](const rice_record& rice_data) {
|
|
return rice_data.eccentricity;
|
|
}, "eccentricity");
|
|
|
|
blt::gp::operation_t op_convex_area([](const rice_record& rice_data) {
|
|
return rice_data.convex_area;
|
|
}, "convex_area");
|
|
|
|
blt::gp::operation_t op_extent([](const rice_record& rice_data) {
|
|
return rice_data.extent;
|
|
}, "extent");
|
|
|
|
constexpr auto fitness_function = [](blt::gp::tree_t& current_tree, blt::gp::fitness_t& fitness, blt::size_t) {
|
|
for (auto& training_case : training_cases)
|
|
{
|
|
auto v = current_tree.get_evaluation_value<float>(training_case);
|
|
switch (training_case.type)
|
|
{
|
|
case rice_type_t::Cammeo:
|
|
if (v >= 0)
|
|
fitness.hits++;
|
|
break;
|
|
case rice_type_t::Osmancik:
|
|
if (v < 0)
|
|
fitness.hits++;
|
|
break;
|
|
}
|
|
}
|
|
fitness.raw_fitness = static_cast<double>(fitness.hits);
|
|
fitness.standardized_fitness = fitness.raw_fitness;
|
|
fitness.adjusted_fitness = 1.0 - (1.0 / (1.0 + fitness.standardized_fitness));
|
|
return static_cast<blt::size_t>(fitness.hits) == training_cases.size();
|
|
};
|
|
|
|
void load_rice_data(std::string_view rice_file_path)
|
|
{
|
|
auto rice_file_data = blt::fs::getLinesFromFile(rice_file_path);
|
|
size_t index = 0;
|
|
while (!blt::string::contains(rice_file_data[index++], "@DATA"))
|
|
{}
|
|
std::vector<rice_record> c;
|
|
std::vector<rice_record> o;
|
|
for (std::string_view v : blt::itr_offset(rice_file_data, index))
|
|
{
|
|
auto data = blt::string::split(v, ',');
|
|
rice_record r{std::stof(data[0]), std::stof(data[1]), std::stof(data[2]), std::stof(data[3]), std::stof(data[4]), std::stof(data[5]),
|
|
std::stof(data[6]), blt::string::contains(data[7], "Cammeo") ? rice_type_t::Cammeo : rice_type_t::Osmancik};
|
|
switch (r.type)
|
|
{
|
|
case rice_type_t::Cammeo:
|
|
c.push_back(r);
|
|
break;
|
|
case rice_type_t::Osmancik:
|
|
o.push_back(r);
|
|
break;
|
|
}
|
|
}
|
|
|
|
blt::size_t total_records = c.size() + o.size();
|
|
blt::size_t training_size = std::min(total_records / 3, 1000ul);
|
|
for (blt::size_t i = 0; i < training_size; i++)
|
|
{
|
|
auto& random = program.get_random();
|
|
auto& vec = random.choice() ? c : o;
|
|
auto pos = random.get_i64(0, static_cast<blt::i64>(vec.size()));
|
|
training_cases.push_back(vec[pos]);
|
|
vec.erase(vec.begin() + pos);
|
|
}
|
|
testing_cases.insert(testing_cases.end(), c.begin(), c.end());
|
|
testing_cases.insert(testing_cases.end(), o.begin(), o.end());
|
|
std::shuffle(testing_cases.begin(), testing_cases.end(), program.get_random());
|
|
BLT_INFO("Created training set of size %ld, testing set is of size %ld", training_size, testing_cases.size());
|
|
}
|
|
|
|
struct test_results_t
|
|
{
|
|
blt::size_t cc = 0;
|
|
blt::size_t co = 0;
|
|
blt::size_t oo = 0;
|
|
blt::size_t oc = 0;
|
|
blt::size_t hits = 0;
|
|
blt::size_t size = 0;
|
|
double percent_hit = 0;
|
|
|
|
test_results_t& operator+=(const test_results_t& a)
|
|
{
|
|
cc += a.cc;
|
|
co += a.co;
|
|
oo += a.oo;
|
|
oc += a.oc;
|
|
hits += a.hits;
|
|
size += a.size;
|
|
percent_hit += a.percent_hit;
|
|
return *this;
|
|
}
|
|
|
|
test_results_t& operator/=(blt::size_t s)
|
|
{
|
|
cc /= s;
|
|
co /= s;
|
|
oo /= s;
|
|
oc /= s;
|
|
hits /= s;
|
|
size /= s;
|
|
percent_hit /= static_cast<double>(s);
|
|
return *this;
|
|
}
|
|
|
|
friend bool operator<(const test_results_t& a, const test_results_t& b)
|
|
{
|
|
return a.hits < b.hits;
|
|
}
|
|
|
|
friend bool operator>(const test_results_t& a, const test_results_t& b)
|
|
{
|
|
return a.hits > b.hits;
|
|
}
|
|
};
|
|
|
|
test_results_t test_individual(blt::gp::individual_t& i)
|
|
{
|
|
test_results_t results;
|
|
|
|
for (auto& testing_case : testing_cases)
|
|
{
|
|
auto result = i.tree.get_evaluation_value<float>(testing_case);
|
|
switch (testing_case.type)
|
|
{
|
|
case rice_type_t::Cammeo:
|
|
if (result >= 0)
|
|
results.cc++; // cammeo cammeo
|
|
else
|
|
results.co++; // cammeo osmancik
|
|
break;
|
|
case rice_type_t::Osmancik:
|
|
if (result < 0)
|
|
results.oo++; // osmancik osmancik
|
|
else
|
|
results.oc++; // osmancik cammeo
|
|
break;
|
|
}
|
|
}
|
|
|
|
results.hits = results.cc + results.oo;
|
|
results.size = testing_cases.size();
|
|
results.percent_hit = static_cast<double>(results.hits) / static_cast<double>(results.size) * 100;
|
|
|
|
return results;
|
|
}
|
|
|
|
int main(int argc, const char** argv)
|
|
{
|
|
blt::arg_parse parser;
|
|
parser.addArgument(blt::arg_builder{"-f", "--file"}.setHelp("File for rice data. Should be in .arff format.").setRequired().build());
|
|
|
|
auto args = parser.parse_args(argc, argv);
|
|
|
|
if (!args.contains("file"))
|
|
{
|
|
BLT_WARN("Please provide path to file with -f or --file");
|
|
return 1;
|
|
}
|
|
|
|
auto rice_file_path = args.get<std::string>("file");
|
|
|
|
BLT_INFO("Starting BLT-GP Rice Classification Example");
|
|
BLT_START_INTERVAL("Rice Classification", "Main");
|
|
BLT_DEBUG("Setup Fitness cases");
|
|
load_rice_data(rice_file_path);
|
|
|
|
BLT_DEBUG("Setup Types and Operators");
|
|
|
|
blt::gp::operator_builder<rice_record> builder{};
|
|
program.set_operations(builder.build(add, sub, mul, pro_div, op_exp, op_log, lit, op_area, op_perimeter, op_major_axis_length,
|
|
op_minor_axis_length, op_eccentricity, op_convex_area, op_extent));
|
|
|
|
BLT_DEBUG("Generate Initial Population");
|
|
auto sel = blt::gp::select_tournament_t{};
|
|
program.generate_population(program.get_typesystem().get_type<float>().id(), fitness_function, sel, sel, sel);
|
|
|
|
BLT_DEBUG("Begin Generation Loop");
|
|
while (!program.should_terminate())
|
|
{
|
|
BLT_TRACE("------------{Begin Generation %ld}------------", program.get_current_generation());
|
|
BLT_TRACE("Creating next generation");
|
|
BLT_START_INTERVAL("Rice Classification", "Gen");
|
|
program.create_next_generation();
|
|
BLT_END_INTERVAL("Rice Classification", "Gen");
|
|
BLT_TRACE("Move to next generation");
|
|
BLT_START_INTERVAL("Rice Classification", "Fitness");
|
|
program.next_generation();
|
|
BLT_TRACE("Evaluate Fitness");
|
|
program.evaluate_fitness();
|
|
BLT_END_INTERVAL("Rice Classification", "Fitness");
|
|
auto& stats = program.get_population_stats();
|
|
BLT_TRACE("Stats:");
|
|
BLT_TRACE("Average fitness: %lf", stats.average_fitness.load());
|
|
BLT_TRACE("Best fitness: %lf", stats.best_fitness.load());
|
|
BLT_TRACE("Worst fitness: %lf", stats.worst_fitness.load());
|
|
BLT_TRACE("Overall fitness: %lf", stats.overall_fitness.load());
|
|
BLT_TRACE("----------------------------------------------");
|
|
std::cout << std::endl;
|
|
}
|
|
|
|
BLT_END_INTERVAL("Rice Classification", "Main");
|
|
|
|
std::vector<std::pair<test_results_t, blt::gp::individual_t*>> results;
|
|
for (auto& i : program.get_current_pop().get_individuals())
|
|
results.emplace_back(test_individual(i), &i);
|
|
std::sort(results.begin(), results.end(), [](const auto& a, const auto& b) {
|
|
return a.first > b.first;
|
|
});
|
|
|
|
BLT_INFO("Best results:");
|
|
for (blt::size_t index = 0; index < 3; index++)
|
|
{
|
|
const auto& record = results[index].first;
|
|
const auto& i = *results[index].second;
|
|
|
|
BLT_INFO("Hits %ld, Total Cases %ld, Percent Hit: %lf", record.hits, record.size, record.percent_hit);
|
|
BLT_DEBUG("Cammeo Cammeo: %ld", record.cc);
|
|
BLT_DEBUG("Cammeo Osmancik: %ld", record.co);
|
|
BLT_DEBUG("Osmancik Osmancik: %ld", record.oo);
|
|
BLT_DEBUG("Osmancik Cammeo: %ld", record.oc);
|
|
BLT_DEBUG("Fitness: %lf, stand: %lf, raw: %lf", i.fitness.adjusted_fitness, i.fitness.standardized_fitness, i.fitness.raw_fitness);
|
|
i.tree.print(program, std::cout);
|
|
|
|
std::cout << "\n";
|
|
}
|
|
|
|
BLT_INFO("Worst Results:");
|
|
for (blt::size_t index = 0; index < 3; index++)
|
|
{
|
|
const auto& record = results[results.size() - 1 - index].first;
|
|
const auto& i = *results[results.size() - 1 - index].second;
|
|
|
|
BLT_INFO("Hits %ld, Total Cases %ld, Percent Hit: %lf", record.hits, record.size, record.percent_hit);
|
|
BLT_DEBUG("Cammeo Cammeo: %ld", record.cc);
|
|
BLT_DEBUG("Cammeo Osmancik: %ld", record.co);
|
|
BLT_DEBUG("Osmancik Osmancik: %ld", record.oo);
|
|
BLT_DEBUG("Osmancik Cammeo: %ld", record.oc);
|
|
BLT_DEBUG("Fitness: %lf, stand: %lf, raw: %lf", i.fitness.adjusted_fitness, i.fitness.standardized_fitness, i.fitness.raw_fitness);
|
|
|
|
std::cout << "\n";
|
|
}
|
|
|
|
BLT_INFO("Average Results");
|
|
test_results_t avg{};
|
|
for (const auto& v : results)
|
|
avg += v.first;
|
|
avg /= results.size();
|
|
BLT_INFO("Hits %ld, Total Cases %ld, Percent Hit: %lf", avg.hits, avg.size, avg.percent_hit);
|
|
BLT_DEBUG("Cammeo Cammeo: %ld", avg.cc);
|
|
BLT_DEBUG("Cammeo Osmancik: %ld", avg.co);
|
|
BLT_DEBUG("Osmancik Osmancik: %ld", avg.oo);
|
|
BLT_DEBUG("Osmancik Cammeo: %ld", avg.oc);
|
|
std::cout << "\n";
|
|
|
|
BLT_PRINT_PROFILE("Rice Classification", blt::PRINT_CYCLES | blt::PRINT_THREAD | blt::PRINT_WALL);
|
|
|
|
#ifdef BLT_TRACK_ALLOCATIONS
|
|
BLT_TRACE("Total Allocations: %ld times with a total of %s", blt::gp::tracker.getAllocations(),
|
|
blt::byte_convert_t(blt::gp::tracker.getAllocatedBytes()).convert_to_nearest_type().to_pretty_string().c_str());
|
|
#endif
|
|
|
|
return 0;
|
|
} |