If called with a positive integer argument, this method will allow you to set number of iterations that train_set will use and will return the network object. If called without an argument, it will …

my $train_dataiter = mx->io->MNISTIter({ image=>"data/train-images-idx3-ubyte", label=>"data/train-labels-idx1-ubyte", data_shape=>[1, 28, 28], batch_size=>$batch_size, …

Creation of AI::NaiveBayes classifier object out of training data is done by AI::NaiveBayes::Learner. For quick start you can use the limited train class method that trains …

# generate train data classifications my string_arrayref $train_classifications = concatenate(for_range('0', (scalar @{$train_data_A})), for_range('1', (scalar @{$train_data_B})));

$edge->attribute('label', 'train'); It is possible to add an edge with a label: $graph->add_edge('Cottbus', 'Berlin', 'my label'); You can also add self-loops: $graph …

If you plan to use the DataSource to train an MLModel, the DataSource also needs a recipe. A recipe describes how each input variable will be used in training an MLModel.

Note: when using a ramp () activatior, train the net at least TWICE on the data set, because the first time the ramp () function searches for the top value in the inputs, and therefore, results …

Perl wrapper for XGBoost library https://github.com/dmlc/xgboost

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string. METHODS for PDL::OpenCV::DMatch Class for matching …

train This method computes the start, emission and transition probabilities from a set of observations and their associated states. The probabilities are simple averages of the passed …