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85 lines
2.1 KiB
C++
85 lines
2.1 KiB
C++
//
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// kNN.cpp
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//
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// Created by Marc Melikyan on 10/2/20.
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//
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#include "knn.h"
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#include "../lin_alg/lin_alg.h"
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#include "../utilities/utilities.h"
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#include <algorithm>
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#include <iostream>
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#include <map>
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MLPPKNN::MLPPKNN(std::vector<std::vector<double>> inputSet, std::vector<double> outputSet, int k) :
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inputSet(inputSet), outputSet(outputSet), k(k) {
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}
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std::vector<double> MLPPKNN::modelSetTest(std::vector<std::vector<double>> X) {
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std::vector<double> y_hat;
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for (int i = 0; i < X.size(); i++) {
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y_hat.push_back(modelTest(X[i]));
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}
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return y_hat;
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}
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int MLPPKNN::modelTest(std::vector<double> x) {
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return determineClass(nearestNeighbors(x));
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}
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double MLPPKNN::score() {
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MLPPUtilities util;
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return util.performance(modelSetTest(inputSet), outputSet);
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}
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int MLPPKNN::determineClass(std::vector<double> knn) {
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std::map<int, int> class_nums;
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for (int i = 0; i < outputSet.size(); i++) {
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class_nums[outputSet[i]] = 0;
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}
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for (int i = 0; i < knn.size(); i++) {
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for (int j = 0; j < outputSet.size(); j++) {
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if (knn[i] == outputSet[j]) {
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class_nums[outputSet[j]]++;
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}
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}
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}
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int max = class_nums[outputSet[0]];
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int final_class = outputSet[0];
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for (int i = 0; i < outputSet.size(); i++) {
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if (class_nums[outputSet[i]] > max) {
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max = class_nums[outputSet[i]];
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}
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}
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for (auto [c, v] : class_nums) {
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if (v == max) {
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final_class = c;
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}
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}
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return final_class;
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}
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std::vector<double> MLPPKNN::nearestNeighbors(std::vector<double> x) {
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MLPPLinAlg alg;
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// The nearest neighbors
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std::vector<double> knn;
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std::vector<std::vector<double>> inputUseSet = inputSet;
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//Perfom this loop unless and until all k nearest neighbors are found, appended, and returned
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for (int i = 0; i < k; i++) {
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int neighbor = 0;
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for (int j = 0; j < inputUseSet.size(); j++) {
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bool isNeighborNearer = alg.euclideanDistance(x, inputUseSet[j]) < alg.euclideanDistance(x, inputUseSet[neighbor]);
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if (isNeighborNearer) {
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neighbor = j;
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}
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}
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knn.push_back(neighbor);
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inputUseSet.erase(inputUseSet.begin() + neighbor); // This is why we maintain an extra input"Use"Set
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}
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return knn;
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}
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