| void Impala::Core::Feature::TryRandomSplit | ( | int & | dimension, | |
| double & | value, | |||
| double & | gain, | |||
| const AnnotatedFeatureTable * | data, | |||
| bool * | filter, | |||
| int | nrClasses, | |||
| Util::Random & | rng | |||
| ) |
Take a random split point and return it and it's gain in the first three reference parameters.
Definition at line 105 of file MakeRandomTree.h.
References Impala::Util::Count(), Gain(), Impala::Core::Table::TableTem< Col1T, Col2T, Col3T, Col4T, Col5T, Col6T, Col7T, Col8T, Col9T >::Get1(), Impala::Core::Table::TableTem< Col1T, Col2T, Col3T, Col4T, Col5T, Col6T, Col7T, Col8T, Col9T >::GetColumn1(), Impala::Util::Random::GetInt(), Impala::Util::IndexOfNth(), Impala::Core::Table::Table::Size(), and SplitSet().
Referenced by FindSplit(), Impala::Core::Feature::TestMakeRandomTree::testFindSplitWithSeed(), and Impala::Core::Feature::TestMakeRandomTree::testTryRandomSplit().
00108 { 00109 dimension = rng.GetInt(data->GetColumn1()->GetVectorLength(0)); 00110 int n = Util::Count(filter, data->Size()); 00111 int index; 00112 if(n==0) 00113 index = rng.GetInt(data->Size()); 00114 else 00115 index = Util::IndexOfNth(filter, data->Size(), rng.GetInt(n)); 00116 value = data->Get1(index)[dimension]; 00117 bool* left = 0; 00118 bool* right = 0; 00119 SplitSet(left, right, dimension, value, data, filter); 00120 gain = Gain(data, nrClasses, left, right); 00121 delete left; 00122 delete right; 00123 }
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