[mlpack-svn] r16986 - mlpack/trunk/src/mlpack/methods/adaboost
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Thu Aug 7 11:19:45 EDT 2014
Author: rcurtin
Date: Thu Aug 7 11:19:45 2014
New Revision: 16986
Log:
Some formatting fixes.
Modified:
mlpack/trunk/src/mlpack/methods/adaboost/adaboost_impl.hpp
Modified: mlpack/trunk/src/mlpack/methods/adaboost/adaboost_impl.hpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/adaboost/adaboost_impl.hpp (original)
+++ mlpack/trunk/src/mlpack/methods/adaboost/adaboost_impl.hpp Thu Aug 7 11:19:45 2014
@@ -77,7 +77,7 @@
sumFinalH.fill(0.0);
// load the initial weights into a 2-D matrix
- const double initWeight = (double) 1 / (data.n_cols * numClasses);
+ const double initWeight = 1.0 / double(data.n_cols * numClasses);
arma::mat D(data.n_cols, numClasses);
D.fill(initWeight);
@@ -110,17 +110,17 @@
// begin calculation of rt
- for (j = 0;j < ht.n_rows; j++)
+ for (j = 0; j < ht.n_rows; j++)
{
- for (k = 0;k < ht.n_cols; k++)
- rt += (D(j,k) * yt(j,k) * ht(j,k));
+ for (k = 0; k < ht.n_cols; k++)
+ rt += (D(j, k) * yt(j, k) * ht(j, k));
}
// end calculation of rt
// std::cout<<"Value of rt is: "<<rt<<"\n";
if (i > 0)
{
- if ( std::abs(rt - crt) < tolerance )
+ if (std::abs(rt - crt) < tolerance)
break;
}
crt = rt;
@@ -130,16 +130,16 @@
// now start modifying weights
- for (j = 0;j < D.n_rows; j++)
+ for (j = 0; j < D.n_rows; j++)
{
- for (k = 0;k < D.n_cols; k++)
+ for (k = 0; k < D.n_cols; k++)
{
// we calculate zt, the normalization constant
- zt += D(j,k) * exp(-1 * alphat * yt(j,k) * ht(j,k));
- D(j,k) = D(j,k) * exp(-1 * alphat * yt(j,k) * ht(j,k));
+ zt += D(j, k) * exp(-alphat * yt(j, k) * ht(j, k));
+ D(j, k) = D(j, k) * exp(-alphat * yt(j, k) * ht(j, k));
// adding to the matrix of FinalHypothesis
- sumFinalH(j,k) += (alphat * ht(j,k));
+ sumFinalH(j, k) += (alphat * ht(j, k));
}
}
@@ -155,7 +155,7 @@
arma::rowvec tempSumFinalH;
arma::uword max_index;
- for (i = 0;i < sumFinalH.n_rows; i++)
+ for (i = 0; i < sumFinalH.n_rows; i++)
{
tempSumFinalH = sumFinalH.row(i);
tempSumFinalH.max(max_index);
@@ -175,7 +175,8 @@
*/
template <typename MatType, typename WeakLearner>
void Adaboost<MatType, WeakLearner>::BuildClassificationMatrix(
- arma::mat& t, const arma::Row<size_t>& l)
+ arma::mat& t,
+ const arma::Row<size_t>& l)
{
int i, j;
@@ -184,9 +185,9 @@
for (j = 0;j < t.n_cols; j++)
{
if (j == l(i))
- t(i,j) = 1.0;
+ t(i, j) = 1.0;
else
- t(i,j) = -1.0;
+ t(i, j) = -1.0;
}
}
}
@@ -203,15 +204,16 @@
*/
template <typename MatType, typename WeakLearner>
void Adaboost<MatType, WeakLearner>::BuildWeightMatrix(
- const arma::mat& D, arma::rowvec& weights)
+ const arma::mat& D,
+ arma::rowvec& weights)
{
int i, j;
weights.fill(0.0);
- for (i = 0;i < D.n_rows; i++)
+ for (i = 0; i < D.n_rows; i++)
{
- for (j = 0;j < D.n_cols; j++)
- weights(i) += D(i,j);
+ for (j = 0; j < D.n_cols; j++)
+ weights(i) += D(i, j);
}
}
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