[mlpack-git] master: Use Row, not vec, for predictions. (d2bcc6b)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Thu Nov 19 16:17:37 EST 2015
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/319205b2f3103187c584db302b1a3683aa2fbfdf...a1dada8ba0f88f14653f09ea8c3ec8b04d982434
>---------------------------------------------------------------
commit d2bcc6b829bc15b3e5d1fe2537cef1876397f06a
Author: Ryan Curtin <ryan at ratml.org>
Date: Thu Nov 19 12:57:31 2015 -0800
Use Row, not vec, for predictions.
>---------------------------------------------------------------
d2bcc6b829bc15b3e5d1fe2537cef1876397f06a
.../methods/softmax_regression/softmax_regression.hpp | 2 +-
.../methods/softmax_regression/softmax_regression_impl.hpp | 13 +++++++------
2 files changed, 8 insertions(+), 7 deletions(-)
diff --git a/src/mlpack/methods/softmax_regression/softmax_regression.hpp b/src/mlpack/methods/softmax_regression/softmax_regression.hpp
index 25f96e8..af83b04 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression.hpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression.hpp
@@ -111,7 +111,7 @@ class SoftmaxRegression
* @param testData Matrix of data points for which predictions are to be made.
* @param predictions Vector to store the predictions in.
*/
- void Predict(const arma::mat& testData, arma::vec& predictions) const;
+ void Predict(const arma::mat& testData, arma::Row<size_t>& predictions) const;
/**
* Computes accuracy of the learned model given the feature data and the
diff --git a/src/mlpack/methods/softmax_regression/softmax_regression_impl.hpp b/src/mlpack/methods/softmax_regression/softmax_regression_impl.hpp
index d21b295..d95cad4 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression_impl.hpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression_impl.hpp
@@ -58,7 +58,8 @@ SoftmaxRegression<OptimizerType>::SoftmaxRegression(
template<template<typename> class OptimizerType>
void SoftmaxRegression<OptimizerType>::Predict(const arma::mat& testData,
- arma::vec& predictions) const
+ arma::Row<size_t>& predictions)
+ const
{
if (testData.n_rows != FeatureSize())
{
@@ -95,16 +96,16 @@ void SoftmaxRegression<OptimizerType>::Predict(const arma::mat& testData,
double maxProbability = 0;
// For each test input.
- for(size_t i = 0; i < testData.n_cols; i++)
+ for (size_t i = 0; i < testData.n_cols; i++)
{
// For each class.
- for(size_t j = 0; j < numClasses; j++)
+ for (size_t j = 0; j < numClasses; j++)
{
// If a higher class probability is encountered, change prediction.
- if(probabilities(j, i) > maxProbability)
+ if (probabilities(j, i) > maxProbability)
{
maxProbability = probabilities(j, i);
- predictions(i) = static_cast<double>(j);
+ predictions(i) = j;
}
}
@@ -118,7 +119,7 @@ double SoftmaxRegression<OptimizerType>::ComputeAccuracy(
const arma::mat& testData,
const arma::Row<size_t>& labels)
{
- arma::vec predictions;
+ arma::Row<size_t> predictions;
// Get predictions for the provided data.
Predict(testData, predictions);
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