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Various bugfixes and additions

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This commit is contained in:
maartenkeijzer 2005-11-24 09:35:34 +00:00
commit 44876f0926
24 changed files with 889 additions and 187 deletions
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16
eo/contrib/mathsym/regression/ErrorMeasure.cpp
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@ -19,9 +19,12 @@
#include <vector>
#include <valarray>
#include "MultiFunction.h"
#include "ErrorMeasure.h"
#include "Dataset.h"
#include "Sym.h"
#include "FunDef.h"
#include "sym_compile.h"
#include "TargetInfo.h"
#include "stats.h"
@ -99,14 +102,19 @@ class ErrorMeasureImpl {
}
vector<ErrorMeasure::result> multi_function_eval(const vector<Sym>& pop) {
if (pop.size() == 0) return vector<ErrorMeasure::result>();
multi_function all = compile(pop);
//MultiFunction all(pop);
std::vector<double> y(pop.size());
Scaling noScaling = Scaling(new NoScaling);
const std::valarray<double>& t = train_info.targets();
cout << "Population size " << pop.size() << endl;
if (measure == ErrorMeasure::mean_squared_scaled) {
std::vector<Var> var(pop.size());
std::vector<Cov> cov(pop.size());
@ -117,6 +125,7 @@ class ErrorMeasureImpl {
vart.update(t[i]);
all(&data.get_inputs(i)[0], &y[0]); // evalutate
//all(data.get_inputs(i), y); // evalutate
for (unsigned j = 0; j < pop.size(); ++j) {
var[j].update(y[j]);
@ -148,6 +157,7 @@ class ErrorMeasureImpl {
double err = vart.get_var() - c / var[i].get_var();
result[i].error = err;
if (!finite(err)) {
//cout << pop[i] << endl;
cout << "b " << b << endl;
cout << "var t " << vart.get_var() << endl;
cout << "var i " << var[i].get_var() << endl;
@ -155,8 +165,9 @@ class ErrorMeasureImpl {
for (unsigned j = 0; j < t.size(); ++j) {
all(&data.get_inputs(i)[0], &y[0]); // evalutate
//all(data.get_inputs(j), y); // evalutate
cout << y[i] << endl;
cout << y[i] << ' ' << ::eval(pop[i], data.get_inputs(j)) << endl;
}
exit(1);
@ -172,8 +183,9 @@ class ErrorMeasureImpl {
for (unsigned i = 0; i < train_cases(); ++i) {
// evaluate
all(&data.get_inputs(i)[0], &y[0]);
//all(data.get_inputs(i), y);
for (unsigned j = 0; j < y.size(); ++j) {
for (unsigned j = 0; j < pop.size(); ++j) {
double diff = y[j] - t[i];
if (measure == ErrorMeasure::mean_squared) { // branch prediction will probably solve this inefficiency
err[j] += diff * diff;