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Project description
HMC-loss
Abstruct
Python-implemented hierarchical multi-class validation metrics: HMC-loss . Original paper is (Bi&Kwok, 2012) .
Install
pip install hmc_loss
Requirement
numpy
Network X
How to use
This metrics is implemented like scikit-learn metrics.
from hmc_loss import hmc_loss_score, get_cost_list import numpy as np # Generate label data(2-D array of numpy) true_label = np.random.randint(2, size(100, 100)) pred_label = np.random.randint(2, size(100, 100)) # Generate test graph(Di-Graph of NetworkX) graph = nx.gnc_graph(100) # Generate element list of graph node label_list = list(range(100)) # Calculate cost of each node in graph cost_list = get_cost_list(graph, 0, label_list) # Calculate HMC-loss hmc_loss_score(true_label, pred_label, graph, 0, label_list, cost_list, alpha=0.5, beta=1.5)
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hmc_loss-1.0.0.tar.gz
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