Run sh ./install.sh. On Ubuntu-based systems run this command as sudo.
Run make and ./gmdl.app to run.
usage: GMDL [options] ...
options:
-i, --inline pass configurations parameters inline instead of reading json file
--stdin reads from stdin (prioritized)
-q, --quiet omits logging when classification fails
--online makes algorithm online
--confusion-matrix prints confusion matrix
--label the index of the column that should be considered the label (int [=0])
--labels the labels of the dataset comma-separated (string [=])
--set the key to the set in the config file that should be read (string [=])
-p, --path the path in which to look for datasets (string [=])
--training the name of the traning set (string [=])
--testing the name of the testing set (string [=])
--config the path to the config json file (string [=./config.json])
--learning_rate the learning rate used to the SGD on the theta exponents (double [=0.01])
--momentum the momentum used to the SGD on the theta exponents (double [=0.9])
--tau the exponent of the prototype distance used to separate classes (double [=1])
--omega the default description length assumed when there is no clue about the data being assessed (double [=-32])
--forgetting_factor the factor by which the samples in the mixture are considered outdated (1 = no forgetting) (double [=1])
--sigma the standard deviation to the noise applied when the covariance matrix is getting close to be singular (double [=1])
--dimension the number of attributes in the dataset (mandatory for online learning) (int [=0])
-?, --help print this message
You can also use a config.json with the same keys as in config.example.json. Note that you must use this json in order to provide the classes being examined.