Python store_matrix Examples

Example #1

File: model_base.py Project: bgruening/EDeN

def main_feature(model_initializer, args):
    iterator = model_initializer.load_data(args)

    from eden.model import ActiveLearningBinaryClassificationModel
    model = ActiveLearningBinaryClassificationModel()
    model.load(args.model_file)
    logger.info(model.get_parameters())
    X = model._data_matrix(iterator)
    store_matrix(matrix=X, output_dir_path=args.output_dir_path, out_file_name='data_matrix', output_format=args.output_format)

Example #2

File: model_base.py Project: bgruening/EDeN

def main_matrix(model_initializer, args):
    iterator = model_initializer.load_data(args)

    from eden.model import ActiveLearningBinaryClassificationModel
    model = ActiveLearningBinaryClassificationModel()
    model.load(args.model_file)
    logger.info(model.get_parameters())
    X = model._data_matrix(iterator)
    K = metrics.pairwise.pairwise_kernels(X, metric='linear')
    store_matrix(matrix=K, output_dir_path=args.output_dir_path, out_file_name='Gram_matrix', output_format=args.output_format)

Example #3

File: model_base.py Project: teresa-m/EDeN

def main_feature(model_initializer, args):
    iterator = model_initializer.load_data(args)

    from eden.model import ActiveLearningBinaryClassificationModel
    model = ActiveLearningBinaryClassificationModel()
    model.load(args.model_file)
    logger.info(model.get_parameters())
    data_matrix = model._data_matrix(iterator)
    store_matrix(matrix=data_matrix,
                 output_dir_path=args.output_dir_path,
                 out_file_name='data_matrix',
                 output_format=args.output_format)

Example #4

File: model_base.py Project: bgruening/EDeN

def main_matrix(model_initializer, args):
    iterator = model_initializer.load_data(args)

    from eden.model import ActiveLearningBinaryClassificationModel
    model = ActiveLearningBinaryClassificationModel()
    model.load(args.model_file)
    logger.info(model.get_parameters())
    X = model._data_matrix(iterator)
    K = metrics.pairwise.pairwise_kernels(X, metric='linear')
    store_matrix(matrix=K,
                 output_dir_path=args.output_dir_path,
                 out_file_name='Gram_matrix',
                 output_format=args.output_format)