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Changed unordered map implementation to uvec implementation

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This commit is contained in:
Anush V Kini
2020-11-01 20:25:28 +05:30
parent 0bdc8b8ef2
commit 76fe709d67
1 changed files with 13 additions and 11 deletions
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src/mlpack/core/data/split_data.hpp
+13 -11
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@@ -14,7 +14,6 @@
#define MLPACK_CORE_DATA_SPLIT_DATA_HPP
#include <mlpack/prereqs.hpp>
#include <unordered_map>
namespace mlpack {
namespace data {
@@ -71,14 +70,14 @@ void StratifiedSplit(const arma::Mat<T>& input,
* The number of 1 labels in our test set = floor(11 * 0.2) = 2.
*
* In our first pass over the dataset,
* we visit each label and keep the count of each label in our unordered map.
* We visit each label and keep count of each label in our 'labelMap' uvec.
*
* We then take a second pass over the dataset.
* We now maintain an additional unordered map to hold the label counts in
* our test set.
* We now maintain an additional uvec 'testLabelMap' to hold the label counts
* of our test set.
*
* In this pass, when we encounter a label we check the test set map for
* the count of this label in the test set.
* In this pass, when we encounter a label we check the 'testLabelMap' uvec
* for the count of this label in the test set.
* If this count is less than the required number of labels in the test set,
* we add the data to the test set and increment the label count in the map.
* If this count is equal to or more than the required count in the test set,
@@ -97,9 +96,12 @@ void StratifiedSplit(const arma::Mat<T>& input,
size_t testIdx = 0;
size_t trainSize = 0;
size_t testSize = 0;
arma::uvec labelMap;
arma::uvec testLabelMap;
U maxLabel = inputLabel.max();
std::unordered_map<U, size_t> labelMap;
std::unordered_map<U, size_t> testLabelMap;
labelMap.zeros(maxLabel+1);
testLabelMap.zeros(maxLabel+1);
arma::uvec order =
arma::linspace<arma::uvec>(0, input.n_cols - 1, input.n_cols);
@@ -115,10 +117,10 @@ void StratifiedSplit(const arma::Mat<T>& input,
labelMap[label] += 1;
}
for (std::pair<U, size_t> countPair : labelMap)
for (arma::uword labelCount : labelMap)
{
testSize += floor(countPair.second * testRatio);
trainSize += countPair.second - floor(countPair.second * testRatio);
testSize += floor(labelCount * testRatio);
trainSize += labelCount - floor(labelCount * testRatio);
}
trainData.set_size(input.n_rows, trainSize);