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template<typename T > |
std::ostream & | machine_learning::operator<< (std::ostream &out, std::vector< std::valarray< T > > const &A) |
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template<typename T > |
std::ostream & | machine_learning::operator<< (std::ostream &out, const std::pair< T, T > &A) |
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template<typename T > |
std::ostream & | machine_learning::operator<< (std::ostream &out, const std::valarray< T > &A) |
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template<typename T > |
std::valarray< T > | machine_learning::insert_element (const std::valarray< T > &A, const T &ele) |
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template<typename T > |
std::valarray< T > | machine_learning::pop_front (const std::valarray< T > &A) |
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template<typename T > |
std::valarray< T > | machine_learning::pop_back (const std::valarray< T > &A) |
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template<typename T > |
void | machine_learning::equal_shuffle (std::vector< std::vector< std::valarray< T > > > &A, std::vector< std::vector< std::valarray< T > > > &B) |
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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) |
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template<typename T > |
void | machine_learning::unit_matrix_initialization (std::vector< std::valarray< T > > &A, const std::pair< size_t, size_t > &shape) |
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template<typename T > |
void | machine_learning::zeroes_initialization (std::vector< std::valarray< T > > &A, const std::pair< size_t, size_t > &shape) |
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template<typename T > |
T | machine_learning::sum (const std::vector< std::valarray< T > > &A) |
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template<typename T > |
std::pair< size_t, size_t > | machine_learning::get_shape (const std::vector< std::valarray< T > > &A) |
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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) |
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template<typename T > |
size_t | machine_learning::argmax (const std::vector< std::valarray< T > > &A) |
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template<typename T > |
std::vector< std::valarray< T > > | machine_learning::apply_function (const std::vector< std::valarray< T > > &A, T(*func)(const T &)) |
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template<typename T > |
std::vector< std::valarray< T > > | machine_learning::operator* (const std::vector< std::valarray< T > > &A, const T &val) |
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template<typename T > |
std::vector< std::valarray< T > > | machine_learning::operator/ (const std::vector< std::valarray< T > > &A, const T &val) |
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template<typename T > |
std::vector< std::valarray< T > > | machine_learning::transpose (const std::vector< std::valarray< T > > &A) |
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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) |
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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) |
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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) |
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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) |
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Various functions for vectors associated with [NeuralNetwork (aka Multilayer Perceptron)] (https://en.wikipedia.org/wiki/Multilayer_perceptron).
- Author
- Deep Raval