0.9
def columns(f,c):
data = pandas.read_csv(f, sep='\t', header=None, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False)
cols = c.split (',')
cols = map(int, cols)
cols = list(map(lambda x: x - 1, cols))
y = data.iloc[:,cols].values
return y
pythonscikit-learnpandasselected_tasks['selected_task'] == 'load'selected_tasks['selected_task'] == 'train'
@misc{fabrizio_costa_2015_15094,
author = {Fabrizio Costa and
Björn Grüning and
gigolo},
title = {EDeN: EDeN - Graph Vectorizer},
month = feb,
year = 2015,
doi = {10.5281/zenodo.15094},
url = {http://dx.doi.org/10.5281/zenodo.15094}
}
}
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
journal={Journal of Machine Learning Research},
volume={12},
pages={2825--2830},
year={2011}
url = {https://github.com/scikit-learn/scikit-learn}
}
@Misc{,
author = {Eric Jones and Travis Oliphant and Pearu Peterson and others},
title = {{SciPy}: Open source scientific tools for {Python}},
year = {2001--},
url = "http://www.scipy.org/",
note = {[Online; accessed 2016-04-09]}
}