12#ifndef ROOT_TMLPAnalyzer
13#define ROOT_TMLPAnalyzer
#define ClassDefOverride(name, id)
The Histogram stack class.
This utility class contains a set of tests usefull when developing a neural network.
Int_t GetNeurons(Int_t layer)
Returns the number of neurons in given layer.
Int_t GetLayers()
Returns the number of layers.
TProfile * DrawTruthDeviation(Int_t outnode=0, Option_t *option="")
Create a profile of the difference of the MLP output minus the true value for a given output node out...
void DrawDInput(Int_t i)
Draws the distribution (on the test sample) of the impact on the network output of a small variation ...
const char * GetOutputNeuronTitle(Int_t out)
Returns the name of any neuron from the output layer.
~TMLPAnalyzer() override
Destructor.
TMLPAnalyzer(TMultiLayerPerceptron &net)
void DrawDInputs()
Draws the distribution (on the test sample) of the impact on the network output of a small variation ...
THStack * DrawTruthDeviationInsOut(Int_t outnode=0, Option_t *option="")
Creates a profile of the difference of the MLP output outnode minus the true value of outnode vs the ...
void CheckNetwork()
Gives some information about the network in the terminal.
void GatherInformations()
Collect information about what is useful in the network.
THStack * DrawTruthDeviations(Option_t *option="")
Creates TProfiles of the difference of the MLP output minus the true value vs the true value,...
TProfile * DrawTruthDeviationInOut(Int_t innode, Int_t outnode=0, Option_t *option="")
Creates a profile of the difference of the MLP output outnode minus the true value of outnode vs the ...
const char * GetInputNeuronTitle(Int_t in)
Returns the name of any neuron from the input layer.
TMultiLayerPerceptron * fNetwork
TTree * GetIOTree() const
TMLPAnalyzer(TMultiLayerPerceptron *net)
TString GetNeuronFormula(Int_t idx)
Returns the formula used as input for neuron (idx) in the first layer.
void DrawNetwork(Int_t neuron, const char *signal, const char *bg)
Draws the distribution of the neural network (using ith neuron).
This class describes a neural network.
This class describes an elementary neuron, which is the basic element for a Neural Network.
Mother of all ROOT objects.
This is a simple weighted bidirectional connection between two neurons.
A TTree represents a columnar dataset.