Results of 1 - 10 of about 149 for [SIMILAR] 16 1024 4096 WITH 16620 neuron WITH 13... (0.482 sec.)
- Set a connection in the network 10000
- « fann_set_weight_array fann_shuffle_train_data » PHP Manual Fann 関数 Set a connection in the network fann_set_weight (PECL fann >= 1.0.0) fann_set_weight — Set a connection in the network 説明 fann_set_weight ( resource $ann , int $from_neuron , int $to_neuron , float $weight ): bool S
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https://man.plustar.jp/php/function.fann-set-weight.html
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- The FANNConnection class 9223
- « fann_train FANNConnection::__construct » PHP Manual FANN The FANNConnection class The FANNConnection class (No version information available, might only be in Git) はじめに FANNConnection is used for the neural network connection. The objects of this class are used in fann_get_connecti
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https://man.plustar.jp/php/class.fannconnection.html
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- The connection constructor 9165
- « FANNConnection FANNConnection::getFromNeuron » PHP Manual FANNConnection The connection constructor FANNConnection::__construct (PECL fann >= 1.0.0) FANNConnection::__construct — The connection constructor 説明 public FANNConnection::__construct ( int $from_neuron , int $to_neuron , fl
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https://man.plustar.jp/php/fannconnection.construct.html
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- Returns the activation steepness for supplied neuron and layer number 7318
- « fann_get_activation_function fann_get_bias_array » PHP Manual Fann 関数 Returns the activation steepness for supplied neuron and layer number fann_get_activation_steepness (PECL fann >= 1.0.0) fann_get_activation_steepness — Returns the activation steepness for supplied neuron and laye
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https://man.plustar.jp/php/function.fann-get-activation-steepness.html
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- Returns the activation function 7318
- « fann_duplicate_train_data fann_get_activation_steepness » PHP Manual Fann 関数 Returns the activation function fann_get_activation_function (PECL fann >= 1.0.0) fann_get_activation_function — Returns the activation function 説明 fann_get_activation_function ( resource $ann , int $layer
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https://man.plustar.jp/php/function.fann-get-activation-function.html
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- Sets the activation function for supplied neuron and layer 7318
- « fann_set_activation_function_output fann_set_activation_steepness_hidden » PHP Manual Fann 関数 Sets the activation function for supplied neuron and layer fann_set_activation_function (PECL fann >= 1.0.0) fann_set_activation_function — Sets the activation function for supplied neuron a
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https://man.plustar.jp/php/function.fann-set-activation-function.html
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- Returns the weight multiplier 5775
- « fann_get_cascade_output_stagnation_epochs fann_get_connection_array » PHP Manual Fann 関数 Returns the weight multiplier fann_get_cascade_weight_multiplier (PECL fann >= 1.0.0) fann_get_cascade_weight_multiplier — Returns the weight multiplier 説明 fann_get_cascade_weight_multiplier (
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https://man.plustar.jp/php/function.fann-get-cascade-weight-multiplier.html
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- Sets the connections weight 5775
- « FANNConnection::getWeight Igbinary » PHP Manual FANNConnection Sets the connections weight FANNConnection::setWeight (PECL fann >= 1.0.0) FANNConnection::setWeight — Sets the connections weight 説明 public FANNConnection::setWeight ( float $weight ): void Sets the connection weight. Th
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https://man.plustar.jp/php/fannconnection.setweight.html
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- Give each connection a random weight between min_weight and max_weight 5775
- « fann_print_error fann_read_train_from_file » PHP Manual Fann 関数 Give each connection a random weight between min_weight and max_weight fann_randomize_weights (PECL fann >= 1.0.0) fann_randomize_weights — Give each connection a random weight between min_weight and max_weight 説明 fann
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https://man.plustar.jp/php/function.fann-randomize-weights.html
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- Sets the weight multiplier 5775
- « fann_set_cascade_output_stagnation_epochs fann_set_error_log » PHP Manual Fann 関数 Sets the weight multiplier fann_set_cascade_weight_multiplier (PECL fann >= 1.0.0) fann_set_cascade_weight_multiplier — Sets the weight multiplier 説明 fann_set_cascade_weight_multiplier ( resource $ann
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https://man.plustar.jp/php/function.fann-set-cascade-weight-multiplier.html
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