Relintai/MLPP
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Added median & mode

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This commit is contained in:
novak_99 2021-05-25 20:33:41 -07:00
parent 17884c6c15
commit 6cb5770a26
3 changed files with 46 additions and 1 deletions
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41
MLPP/Stat/Stat.cpp
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@ -6,6 +6,9 @@
#include "Stat.hpp"
#include "Activation/Activation.hpp"
#include "Data/Data.hpp"
#include <algorithm>
#include <map>
#include <cmath>
namespace MLPP{
@ -25,6 +28,44 @@ namespace MLPP{
return sum / x.size();
}
double Stat::median(std::vector<double> x){
double center = double(x.size())/double(2);
std::vector<double> original_vec = x;
sort(x.begin(), x.end());
if(x.size() % 2 == 0){
return mean({x[center - 1], x[center]});
}
else{
return x[center - 1 + 0.5];
}
x = original_vec;
}
std::vector<double> Stat::mode(std::vector<double> x){
Data data;
std::vector<double> x_set = data.vecToSet(x);
std::map<double, int> element_num;
for(int i = 0; i < x_set.size(); i++){
element_num[x[i]] = 0;
}
for(int i = 0; i < x.size(); i++){
element_num[x[i]]++;
}
std::vector<double> modes;
double max_num = element_num[x_set[0]];
for(int i = 0; i < x_set.size(); i++){
if(element_num[x_set[i]] > max_num){
max_num = element_num[x_set[i]];
modes.clear();
modes.push_back(x_set[i]);
}
else if(element_num[x_set[i]] == max_num){
modes.push_back(x_set[i]);
}
}
return modes;
}
double Stat::variance(std::vector<double> x){
double sum = 0;
for(int i = 0; i < x.size(); i++){

2
MLPP/Stat/Stat.hpp
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@ -18,6 +18,8 @@ namespace MLPP{
// Statistical Functions
double mean(std::vector <double> x);
double median(std::vector<double> x);
std::vector<double> mode(std::vector<double> x);
double variance(std::vector <double> x);
double covariance(std::vector <double> x, std::vector <double> y);
double correlation(std::vector <double> x, std::vector<double> y);

4
main.cpp
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@ -76,11 +76,13 @@ int main() {
// std::vector<double> outputSet = {0,1,1,0};
// // STATISTICS
// std::vector<double> x = {1,2,3,4,5,6,7,8,9,10};
// std::vector<double> x = {1,2,3,4,5,6,7,8,9,1};
// std::vector<double> y = {10,9,8,7,6,5,4,3,2,1};
// std::vector<double> w = {0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1};
// std::cout << "Arithmetic Mean: " << stat.mean(x) << std::endl;
// std::cout << "Median: " << stat.median(x) << std::endl;
// alg.printVector(stat.mode(x));
// std::cout << "Variance: " << stat.variance(x) << std::endl;
// std::cout << "Covariance: " << stat.covariance(x, y) << std::endl;
// std::cout << "Correlation: " << stat.correlation(x, y) << std::endl;