def data_sparse(filename, nbr_features):
''' This function takes as argument a file representing a sparse matrix
sparse_matrix[i][j] = "a:b" means matrix[i][a] = basename and load it with the loadsvm load_svmlight_file
'''
return data_converter.file_to_libsvm(filename=filename,
data_binary=False,
n_features=nbr_features)
def data_binary_sparse(filename, nbr_features):
''' This fuction takes as argument a file representing a sparse binary matrix
sparse_binary_matrix[i][j] = "a"and transforms it temporarily into file svmlibs format( <index2>:<value2>)
to load it with the loadsvm load_svmlight_file
'''
return data_converter.file_to_libsvm(filename=filename,
data_binary=True,
n_features=nbr_features)
def data_binary_sparse(filename, nbr_features):
''' This fuction takes as argument a file representing a sparse binary matrix
sparse_binary_matrix[i][j] = "a"and transforms it temporarily into file svmlibs format( <index2>:<value2>)
to load it with the loadsvm load_svmlight_file
'''
return data_converter.file_to_libsvm(filename=filename, data_binary=True, n_features=nbr_features)
def data_sparse(filename, nbr_features):
''' This function takes as argument a file representing a sparse matrix
sparse_matrix[i][j] = "a:b" means matrix[i][a] = basename and load it with the loadsvm load_svmlight_file
'''
return data_converter.file_to_libsvm(filename=filename, data_binary=False, n_features=nbr_features)