TheAlgorithms/C++ 1.0.0
All the algorithms implemented in C++
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vector_ops.hpp File Reference

Various functions for vectors associated with [NeuralNetwork (aka Multilayer Perceptron)] (https://en.wikipedia.org/wiki/Multilayer_perceptron). More...

#include <algorithm>
#include <chrono>
#include <iostream>
#include <random>
#include <valarray>
#include <vector>
Include dependency graph for vector_ops.hpp:
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Go to the source code of this file.

Namespaces

namespace  machine_learning
 A* search algorithm
 

Functions

template<typename T >
std::ostream & machine_learning::operator<< (std::ostream &out, std::vector< std::valarray< T > > const &A)
 
template<typename T >
std::ostream & machine_learning::operator<< (std::ostream &out, const std::pair< T, T > &A)
 
template<typename T >
std::ostream & machine_learning::operator<< (std::ostream &out, const std::valarray< T > &A)
 
template<typename T >
std::valarray< T > machine_learning::insert_element (const std::valarray< T > &A, const T &ele)
 
template<typename T >
std::valarray< T > machine_learning::pop_front (const std::valarray< T > &A)
 
template<typename T >
std::valarray< T > machine_learning::pop_back (const std::valarray< T > &A)
 
template<typename T >
void machine_learning::equal_shuffle (std::vector< std::vector< std::valarray< T > > > &A, std::vector< std::vector< std::valarray< T > > > &B)
 
template<typename T >
void machine_learning::uniform_random_initialization (std::vector< std::valarray< T > > &A, const std::pair< size_t, size_t > &shape, const T &low, const T &high)
 
template<typename T >
void machine_learning::unit_matrix_initialization (std::vector< std::valarray< T > > &A, const std::pair< size_t, size_t > &shape)
 
template<typename T >
void machine_learning::zeroes_initialization (std::vector< std::valarray< T > > &A, const std::pair< size_t, size_t > &shape)
 
template<typename T >
machine_learning::sum (const std::vector< std::valarray< T > > &A)
 
template<typename T >
std::pair< size_t, size_t > machine_learning::get_shape (const std::vector< std::valarray< T > > &A)
 
template<typename T >
std::vector< std::vector< std::valarray< T > > > machine_learning::minmax_scaler (const std::vector< std::vector< std::valarray< T > > > &A, const T &low, const T &high)
 
template<typename T >
size_t machine_learning::argmax (const std::vector< std::valarray< T > > &A)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::apply_function (const std::vector< std::valarray< T > > &A, T(*func)(const T &))
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::operator* (const std::vector< std::valarray< T > > &A, const T &val)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::operator/ (const std::vector< std::valarray< T > > &A, const T &val)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::transpose (const std::vector< std::valarray< T > > &A)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::operator+ (const std::vector< std::valarray< T > > &A, const std::vector< std::valarray< T > > &B)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::operator- (const std::vector< std::valarray< T > > &A, const std::vector< std::valarray< T > > &B)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::multiply (const std::vector< std::valarray< T > > &A, const std::vector< std::valarray< T > > &B)
 
template<typename T >
std::vector< std::valarray< T > > machine_learning::hadamard_product (const std::vector< std::valarray< T > > &A, const std::vector< std::valarray< T > > &B)
 

Detailed Description

Various functions for vectors associated with [NeuralNetwork (aka Multilayer Perceptron)] (https://en.wikipedia.org/wiki/Multilayer_perceptron).

Author
Deep Raval

Definition in file vector_ops.hpp.