[mlpack] 11/40: spelling
Barak A. Pearlmutter
barak+git at pearlmutter.net
Mon Feb 15 19:34:23 UTC 2016
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commit 818f132ee61b6d9053c8bf95f5999d1fc2243778
Author: Barak A. Pearlmutter <barak+git at cs.nuim.ie>
Date: Sun Aug 17 09:03:13 2014 +0200
spelling
Gbp-Pq: Name 0002-spelling.patch
---
doc/tutorials/amf/amf.txt | 8 ++++----
src/mlpack/core/tree/ballbound_impl.hpp | 2 +-
src/mlpack/core/tree/cosine_tree/cosine_tree.cpp | 2 +-
src/mlpack/methods/amf/init_rules/average_init.hpp | 4 ++--
src/mlpack/methods/amf/init_rules/random_acol_init.hpp | 2 +-
src/mlpack/methods/amf/init_rules/random_init.hpp | 4 ++--
.../amf/termination_policies/simple_tolerance_termination.hpp | 2 +-
.../amf/termination_policies/validation_RMSE_termination.hpp | 2 +-
src/mlpack/methods/lsh/lsh_search.hpp | 4 ++--
.../methods/softmax_regression/softmax_regression_function.cpp | 2 +-
.../methods/sparse_autoencoder/sparse_autoencoder_function.hpp | 2 +-
src/mlpack/tests/cosine_tree_test.cpp | 2 +-
12 files changed, 18 insertions(+), 18 deletions(-)
diff --git a/doc/tutorials/amf/amf.txt b/doc/tutorials/amf/amf.txt
index abb4c03..bc4f8ed 100644
--- a/doc/tutorials/amf/amf.txt
+++ b/doc/tutorials/amf/amf.txt
@@ -72,14 +72,14 @@ the threshold or the number of iterations goes beyond the threshold, positive
termination signal is passed to AMF.
In SimpleToleranceTermination, termination criterion is met when increase in
-residue value drops below the given tolerance. To accomodate spikes, certain
+residue value drops below the given tolerance. To accommodate spikes, certain
number of successive residue drops are accepted. Secondary termination criterion
terminates algorithm when iteration count goes beyond the threshold.
ValidationRMSETermination divids the data into 2 sets, training set and
validation set. Entries of validation set are nullifed in the input matrix.
Termination criterion is met when increase in validation set RMSe value drops
-below the given tolerance. To accomodate spikes certain number of successive
+below the given tolerance. To accommodate spikes certain number of successive
validation RMSE drops are accepted. This upper imit on successive drops can be
adjusted with reverseStepCount. Secondary termination criterion terminates
algorithm when iteration count goes above the threshold. Though this termination
@@ -101,7 +101,7 @@ The AMF class comes with 2 initialization policies
RandomInitialization initializes matrices W and H with random uniform distribution
while RandomAcolInitialization initializes the W matrix by averaging p randomly
-chosen columns of V. In case of RandomAcolIntialization, p is a template parameter.
+chosen columns of V. In case of RandomAcolInitialization, p is a template parameter.
To implement their own initialization policy, users need to define the following
function in their class.
@@ -160,7 +160,7 @@ int main()
}
@endcode
-NMFALSFactorizer uses SimpleResidueTermination which is most prefered with
+NMFALSFactorizer uses SimpleResidueTermination which is most preferred with
Non-Negative Matrix factorizers. Initialization of W and H in NMFALSFactorizer
is random. The Apply function returns the residue obtained by comparing the
constructed matrix W * H with the original matrix V.
diff --git a/src/mlpack/core/tree/ballbound_impl.hpp b/src/mlpack/core/tree/ballbound_impl.hpp
index 58c5b5a..170e09c 100644
--- a/src/mlpack/core/tree/ballbound_impl.hpp
+++ b/src/mlpack/core/tree/ballbound_impl.hpp
@@ -263,7 +263,7 @@ BallBound<VecType, TMetricType>::operator|=(const MatType& data)
if (dist > radius)
{
// Move towards the new point and increase the radius just enough to
- // accomodate the new point.
+ // accommodate the new point.
arma::vec diff = data.col(i) - center;
center += ((dist - radius) / (2 * dist)) * diff;
radius = 0.5 * (dist + radius);
diff --git a/src/mlpack/core/tree/cosine_tree/cosine_tree.cpp b/src/mlpack/core/tree/cosine_tree/cosine_tree.cpp
index 789ea9c..a1a06a5 100644
--- a/src/mlpack/core/tree/cosine_tree/cosine_tree.cpp
+++ b/src/mlpack/core/tree/cosine_tree/cosine_tree.cpp
@@ -332,7 +332,7 @@ void CosineTree::ColumnSamplesLS(std::vector<size_t>& sampledIndices,
cDistribution(i+1) = cDistribution(i) + l2NormsSquared(i) / frobNormSquared;
}
- // Intialize sizes of the 'sampledIndices' and 'probabilities' vectors.
+ // Initialize sizes of the 'sampledIndices' and 'probabilities' vectors.
sampledIndices.resize(numSamples);
probabilities.zeros(numSamples);
diff --git a/src/mlpack/methods/amf/init_rules/average_init.hpp b/src/mlpack/methods/amf/init_rules/average_init.hpp
index 6fe8dce..f0bb39a 100644
--- a/src/mlpack/methods/amf/init_rules/average_init.hpp
+++ b/src/mlpack/methods/amf/init_rules/average_init.hpp
@@ -2,7 +2,7 @@
* @file averge_init.hpp
* @author Sumedh Ghaisas
*
- * Intialization rule for Alternating Matrix Factorization.
+ * Initialization rule for Alternating Matrix Factorization.
*
* This file is part of mlpack 2.0.0.
*
@@ -68,7 +68,7 @@ class AverageInitialization
avgV = sqrt(((avgV / (n * m)) - min) / r);
- // Intialize to random values.
+ // Initialize to random values.
W.randu(n, r);
H.randu(r, m);
diff --git a/src/mlpack/methods/amf/init_rules/random_acol_init.hpp b/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
index 3444089..b38666f 100644
--- a/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
+++ b/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
@@ -2,7 +2,7 @@
* @file random_acol_init.hpp
* @author Mohan Rajendran
*
- * Intialization rule for Alternating Matrix Factorization.
+ * Initialization rule for Alternating Matrix Factorization.
*
* This file is part of mlpack 2.0.0.
*
diff --git a/src/mlpack/methods/amf/init_rules/random_init.hpp b/src/mlpack/methods/amf/init_rules/random_init.hpp
index 2217462..9b3b9bc 100644
--- a/src/mlpack/methods/amf/init_rules/random_init.hpp
+++ b/src/mlpack/methods/amf/init_rules/random_init.hpp
@@ -2,7 +2,7 @@
* @file random_init.hpp
* @author Mohan Rajendran
*
- * Intialization rule for alternating matrix forization (AMF). This simple
+ * Initialization rule for alternating matrix forization (AMF). This simple
* initialization is performed by assigning a random matrix to W and H.
*
* This file is part of mlpack 2.0.0.
@@ -48,7 +48,7 @@ class RandomInitialization
const size_t n = V.n_rows;
const size_t m = V.n_cols;
- // Intialize to random values.
+ // Initialize to random values.
W.randu(n, r);
H.randu(r, m);
}
diff --git a/src/mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp b/src/mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp
index 4bb7072..1b2f64c 100644
--- a/src/mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp
+++ b/src/mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp
@@ -22,7 +22,7 @@ namespace amf {
/**
* This class implements residue tolerance termination policy. Termination
* criterion is met when increase in residue value drops below the given tolerance.
- * To accomodate spikes certain number of successive residue drops are accepted.
+ * To accommodate spikes certain number of successive residue drops are accepted.
* This upper imit on successive drops can be adjusted with reverseStepCount.
* Secondary termination criterion terminates algorithm when iteration count
* goes above the threshold.
diff --git a/src/mlpack/methods/amf/termination_policies/validation_RMSE_termination.hpp b/src/mlpack/methods/amf/termination_policies/validation_RMSE_termination.hpp
index 00c42e9..ed65045 100644
--- a/src/mlpack/methods/amf/termination_policies/validation_RMSE_termination.hpp
+++ b/src/mlpack/methods/amf/termination_policies/validation_RMSE_termination.hpp
@@ -26,7 +26,7 @@ namespace amf
* The input data matrix is divided into 2 sets, training set and validation set.
* Entries of validation set are nullifed in the input matrix. Termination
* criterion is met when increase in validation set RMSe value drops below the
- * given tolerance. To accomodate spikes certain number of successive validation
+ * given tolerance. To accommodate spikes certain number of successive validation
* RMSE drops are accepted. This upper imit on successive drops can be adjusted
* with reverseStepCount. Secondary termination criterion terminates algorithm
* when iteration count goes above the threshold.
diff --git a/src/mlpack/methods/lsh/lsh_search.hpp b/src/mlpack/methods/lsh/lsh_search.hpp
index 2e895b2..428aca2 100644
--- a/src/mlpack/methods/lsh/lsh_search.hpp
+++ b/src/mlpack/methods/lsh/lsh_search.hpp
@@ -192,8 +192,8 @@ class LSHSearch
* standard hash.
*
* This function does not have any parameters and relies on parameters which
- * are private members of this class, intialized during the class
- * intialization.
+ * are private members of this class, initialized during the class
+ * initialization.
*/
void BuildHash();
diff --git a/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp b/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
index e0faeb9..68fae7f 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
@@ -27,7 +27,7 @@ SoftmaxRegressionFunction::SoftmaxRegressionFunction(
lambda(lambda),
fitIntercept(fitIntercept)
{
- // Intialize the parameters to suitable values.
+ // Initialize the parameters to suitable values.
initialPoint = InitializeWeights();
// Calculate the label matrix.
diff --git a/src/mlpack/methods/sparse_autoencoder/sparse_autoencoder_function.hpp b/src/mlpack/methods/sparse_autoencoder/sparse_autoencoder_function.hpp
index e9121a6..7cd7dba 100644
--- a/src/mlpack/methods/sparse_autoencoder/sparse_autoencoder_function.hpp
+++ b/src/mlpack/methods/sparse_autoencoder/sparse_autoencoder_function.hpp
@@ -149,7 +149,7 @@ class SparseAutoencoderFunction
private:
//! The matrix of data points.
const arma::mat& data;
- //! Intial parameter vector.
+ //! Initial parameter vector.
arma::mat initialPoint;
//! Size of the visible layer.
size_t visibleSize;
diff --git a/src/mlpack/tests/cosine_tree_test.cpp b/src/mlpack/tests/cosine_tree_test.cpp
index 5167c2a..b3ee797 100644
--- a/src/mlpack/tests/cosine_tree_test.cpp
+++ b/src/mlpack/tests/cosine_tree_test.cpp
@@ -55,7 +55,7 @@ BOOST_AUTO_TEST_CASE(CosineTreeNoSplit)
*/
BOOST_AUTO_TEST_CASE(CosineNodeCosineSplit)
{
- // Intialize constants required for the test.
+ // Initialize constants required for the test.
const size_t numRows = 500;
const size_t numCols = 1000;
--
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