public virtual double approxLearnSamples(KnowlegeBaseSARules Solution) //attention only for multicore processor optimized
{
Requires(Solution != null);
double sum = LearnSamplesSet.DataRows.AsParallel().WithExecutionMode(ParallelExecutionMode.ForceParallelism).Select(x => Math.Pow(x.DoubleOutput - approx_base(x.InputAttributeValue, Solution), 2)).Sum();
return((double)Math.Sqrt(sum) / (double)LearnSamplesSet.CountSamples);
}
public virtual double approxTestSamples(KnowlegeBaseSARules forTest)
{
Requires(forTest != null);
double sum = TestSamplesSet.DataRows.AsParallel().WithExecutionMode(ParallelExecutionMode.ForceParallelism).Select(x => Math.Pow(x.DoubleOutput - approx_base(x.InputAttributeValue, forTest), 2)).Sum();
return((double)Math.Sqrt(sum) / (double)TestSamplesSet.CountSamples);
}
public virtual double approx_base(double[] object_c, KnowlegeBaseSARules Solution)
{
Requires(object_c != null);
Requires(Solution != null);
double sum = 0;
double sum2 = 0;
foreach (var rule in Solution.RulesDatabase)
{
double mul = rule.ListTermsInRule.Where(x => AcceptedFeatures[x.NumVar]).Select(x => x.LevelOfMembership(object_c)).Aggregate(1.0, (g, h) => g * h);
sum2 += mul;
sum += mul * rule.IndependentConstantConsequent;
}
if (sum2 != 0)
{
return(sum / (double)sum2);
}
return(double.MaxValue);
}
public KnowlegeBaseSARules(KnowlegeBaseSARules source, List <bool> used_rules = null)
{
for (int i = 0; i < source.TermsSet.Count; i++)
{
Term temp_term = new Term(source.TermsSet[i]);
TermsSet.Add(temp_term);
}
for (int j = 0; j < source.RulesDatabase.Count; j++)
{
if ((used_rules == null) || (used_rules[j]))
{
int[] order = new int[source.RulesDatabase[j].ListTermsInRule.Count];
for (int k = 0; k < source.RulesDatabase[j].ListTermsInRule.Count; k++)
{
Term temp_term = source.RulesDatabase[j].ListTermsInRule[k];
order[k] = source.TermsSet.FindIndex(x => x == temp_term);
}
double temp_DoubleOutputs = source.RulesDatabase[j].IndependentConstantConsequent;
SARule temp_rule = new SARule(TermsSet, order, temp_DoubleOutputs);
RulesDatabase.Add(temp_rule);
}
}
}
public override double ErrorLearnSamples(KnowlegeBaseRules Source)
{
KnowlegeBaseSARules temp = Source as KnowlegeBaseSARules;
return(approxLearnSamples(temp));
}
