module Ai4cr::NeuralNetwork::Cmn::MiniNetConcerns::CalcGuess

Direct including types

Defined in:

ai4cr/neural_network/cmn/mini_net_concerns/calc_guess.cr

Instance Method Summary

Instance Method Detail

def bias_default #

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def bias_default=(bias_default) #

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def bias_disabled #

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def bias_disabled=(bias_disabled) #

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def deriv_scale : Float64 #

for Prelu

TODO set deriv_scale based on ?


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def deriv_scale=(deriv_scale : Float64) #

for Prelu

TODO set deriv_scale based on ?


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def eval(inputs_given) #

steps for 'eval' aka 'guess':


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def guesses_as_is #

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def guesses_best #

misc guesses*


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def guesses_bottom_n(n = @outputs_guessed.size) #

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def guesses_ceiled #

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def guesses_rounded #

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def guesses_sorted #

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def guesses_top_n(n = @outputs_guessed.size) #

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def height #

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def height_considering_bias #

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def height_indexes #

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def init_net_re_guess #

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def init_net_re_structure #

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def inputs_given #

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def inputs_given=(inputs_given) #

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def learning_rate : Float64 #

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def learning_rate=(learning_rate : Float64) #

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def learning_styles #

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def learning_styles=(learning_styles) #

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def load_inputs(inputs_given) #

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def momentum : Float64 #

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def momentum=(momentum : Float64) #

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def outputs_guessed #

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def outputs_guessed=(outputs_guessed) #

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def propagation_function #

ameba:disable Metrics/CyclomaticComplexity


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def step_calc_forward #

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def step_load_inputs(inputs_given) #

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def validate_inputs(inputs, height_expected) #

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def validate_outputs(outputs, width_expected) #

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def weight_init_scale : Float64 #

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def weight_init_scale=(weight_init_scale : Float64) #

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def weights #

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def weights=(weights) #

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def width #

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def width_indexes #

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