43 unsigned n_inp = from.size() - n_out;
52 for(
unsigned i = 0; i < n_inp; ++i)
59 for(
unsigned i = n_inp, e = from.size(); i < e; ++i)
61 unsigned idx = i - n_inp;
void set_bounds(Bounds &from, Bounds &to)
Sets the bounds from already built Bound objects.
void load_info_file(const std::string &info_path)
Loads the bounds info file.
Bounds from
Original data bounds.
void run()
Runs the network with the current input setted by inp().
double & inp(unsigned idx)
Accessor to get/set an input value.
double out(unsigned idx)
Accessor to get an output value.
void load_file(std::ifstream &inp)
Reads the scaling information from a file stream.
void scale()
Scales the data, neuron per neuron, using the current from and to bounds.
Bounds to
Scaled data bounds.
Data scaling information, for all input and output neurons.
const Row & run(const Row &in, bool calc_error=false)
Propagates an input in the network.
void load_file(const std::string &path)
Loads the network contents from a file.
unsigned size() const
Returns the number of layers.
Data used in training, validation and testing.
void descale()
Descales the data.
Row & add()
Adds a row to the data, returning a reference to it.