Regression.zip_provideu96_stream19h_局部线性回归_线性回归

#include <iostream> #include "LinearRegression.h" using namespace std; void chirps_vs_temp() { double chirps[] = {20, 16, 20, 18, 17, 16, 15, 17, 15, 16, 15, 17, 16, 17, 14}; double temperatures[] = {89, 72, 93, 84, 81, 75, 70, 82, 69, 83, 80, 83, 81, 84, 76}; LinearRegression lr(chirps, temperatures, 15); cout << "Enter learning rate alpha (default: 0.01): "; double alpha; cin >> alpha; cout << "Enter number of iterations (default: 1500): "; int iterations; cin >> iterations; cout << "Training model..." << endl; lr.train(alpha, iterations); cout << "Model has been trained, enter number of chirps: "; double x; cin >> x; double temperature = lr.predict(x); cout << "Estimated temperature: " << temperature << " F" << endl; } void sand_vs_slope() { double diameter[] = {0.17, 0.19, 0.22, 0.235, 0.235, 0.3, 0.35, 0.42, 0.85}; double slope[] = {0.63, 0.7, 0.82, 0.88, 1.15, 1.5, 4.4, 7.3, 11.3}; LinearRegression lr(diameter, slope, 9); cout << "Enter learning rate alpha (default: 0.01): "; double alpha; cin >> alpha; cout << "Enter number of iterations (default: 1500): "; int iterations; cin >> iterations; cout << "Training model..." << endl; lr.train(alpha, iterations); cout << "Model has been trained, enter diameter: "; double x; cin >> x; double temperature = lr.predict(x); cout << "Estimated slope: " << temperature << endl; } void fires_vs_theft() { double fires[] = {6.2, 9.5, 10.5, 7.7, 8.6, 34.1, 11, 6.9, 7.3, 15.1, 29.1, 2.2, 5.7, 2, 2.5, 4, 5.4, 2.2, 7.2, 15.1, 16.5, 18.4, 36.2, 39.7, 18.5, 23.3, 12.2, 5.6, 21.8, 21.6, 9, 3.6, 5, 28.6, 17.4, 11.3, 3.4, 11.9, 10.5, 10.7, 10.8, 4.8}; double theft[] = {29, 44, 36, 37, 53, 68, 75, 18, 31, 25, 34, 14, 11, 11, 22, 16, 27, 9, 29, 30, 40, 32, 41, 147, 22, 29, 46, 23, 4, 31, 39, 15, 32, 27, 32, 34, 17, 46, 42, 43, 34, 19}; LinearRegression lr(fires, theft, 42); cout << "Enter learning rate alpha (default: 0.01): "; double alpha; cin >> alpha; cout << "Enter number of iterations (default: 1500): "; int iterations; cin >> iterations; cout << "Training model..." << endl; lr.train(alpha, iterations); cout << "Model has been trained, enter fires: "; double x; cin >> x; double temperature = lr.predict(x); cout << "Estimated theft: " << temperature << endl; } int main() { while (1) { cout << "Choose example: " << endl; cout << "0: Exit" << endl; cout << "1. Cricket chirps/sec vs temperature in degrees fahrenheit" << endl; cout << "2. Diameter (mm) of sand granules vs slope on natural beach (degrees)" << endl; cout << "3. Fires per 1000 houses vs thefts per 1000 population in Chicago" << endl; int opt; cin >> opt; if (!opt) { break; } cout << endl; switch (opt) { case 1: chirps_vs_temp(); break; case 2: sand_vs_slope(); break; case 3: fires_vs_theft(); break; default: break; } cout << endl << endl; } return 0; }