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MNT remove __future__ imports (scikit-learn#12791)
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benchmarks/bench_20newsgroups.py

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from __future__ import print_function, division
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from time import time
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import argparse
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import numpy as np

benchmarks/bench_covertype.py

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[1] https://archive.ics.uci.edu/ml/datasets/Covertype
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"""
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from __future__ import division, print_function
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# Author: Peter Prettenhofer <[email protected]>
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# Arnaud Joly <[email protected]>

benchmarks/bench_isotonic.py

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This allows the scaling of the algorithm with the problem size to be
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visualized and understood.
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"""
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from __future__ import print_function
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import numpy as np
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import gc
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from datetime import datetime

benchmarks/bench_mnist.py

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CART 20.69s 0.02s 0.1219
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dummy 0.00s 0.01s 0.8973
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"""
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from __future__ import division, print_function
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# Author: Issam H. Laradji
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# Arnaud Joly <[email protected]>

benchmarks/bench_multilabel_metrics.py

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"""
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A comparison of multilabel target formats and metrics over them
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"""
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from __future__ import division
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from __future__ import print_function
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from timeit import timeit
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from functools import partial

benchmarks/bench_plot_fastkmeans.py

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from __future__ import print_function
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from collections import defaultdict
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from time import time
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benchmarks/bench_plot_lasso_path.py

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The input data is mostly low rank but is a fat infinite tail.
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"""
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from __future__ import print_function
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from collections import defaultdict
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import gc
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import sys

benchmarks/bench_plot_nmf.py

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# Anthony Di Franco (projected gradient, Python and NumPy port)
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# License: BSD 3 clause
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from __future__ import print_function
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from time import time
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import sys
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import warnings

benchmarks/bench_plot_omp_lars.py

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The input data is mostly low rank but is a fat infinite tail.
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"""
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from __future__ import print_function
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import gc
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import sys
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from time import time

benchmarks/bench_random_projections.py

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Benchmarks for random projections.
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"""
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from __future__ import division
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from __future__ import print_function
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import gc
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import sys
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import optparse

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