def __init__(self,
domain,
discovery_threshold,
initial_representation,
sparsify=True,
discretization=20,
debug=0,
useCache=0,
maxBatchDiscovery=1,
batchThreshold=0,
iFDDPlus=1,
seed=1):
self.iFDD_features = {}
self.iFDD_potentials = {}
self.featureIndex2feature = {}
self.cache = {}
self.discovery_threshold = discovery_threshold
self.sparsify = sparsify
self.setBinsPerDimension(domain, discretization)
self.features_num = initial_representation.features_num
self.debug = debug
self.useCache = useCache
self.maxBatchDiscovery = maxBatchDiscovery
self.batchThreshold = batchThreshold
self.sortediFDDFeatures = PriorityQueueWithNovelty()
self.initial_representation = initial_representation
self.iFDDPlus = iFDDPlus
self.isDynamic = True
self.addInitialFeatures()
super(iFDD, self).__init__(domain, discretization, seed)
def __init__(self, domain, kernel, active_threshold, discover_threshold,
kernel_args=[], normalization=True, sparsify=True,
max_active_base_feat=2, max_base_feat_sim=0.7):
super(KernelizediFDD, self).__init__(domain)
self.kernel = kernel
self.kernel_args = kernel_args
self.active_threshold = active_threshold
self.discover_threshold = discover_threshold
self.normalization = normalization
self.sparsify = sparsify
self.sorted_ids = PriorityQueueWithNovelty()
self.max_active_base_feat = max_active_base_feat
self.max_base_feat_sim = max_base_feat_sim
self.candidates = {}
self.features = []
self.base_features_ids = []
self.max_relevance = 0.
