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| <!DOCTYPE html> | |
| <html> | |
| <head><meta charset="utf-8" /> | |
| <title>dominion</title> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script> | |
| <style type="text/css"> | |
| /*! |
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| import os | |
| from dask.callbacks import Callback | |
| from dask.dot import dot_graph | |
| class Track(Callback): | |
| def __init__(self, path='dasks', save_every=1): | |
| self.path = path | |
| self.save_every = save_every |
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| import datetime | |
| import dask | |
| from dask.multiprocessing import get as mp_get | |
| from dask import delayed | |
| from lxml import etree | |
| from multiprocessing import Pool | |
| N = 10000 | |
| num_workers = 4 |
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| from __future__ import print_function, absolute_import, division | |
| import numbers | |
| import warnings | |
| import dask.array as da | |
| import numpy as np | |
| from scipy.optimize import fmin_l_bfgs_b | |
| from sklearn import linear_model | |
| from sklearn.preprocessing import LabelEncoder |
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| /* Generated by Cython 0.25.2 */ | |
| /* BEGIN: Cython Metadata | |
| { | |
| "distutils": { | |
| "depends": [ | |
| "C:\\Users\\builder\\Miniconda2\\envs\\crick\\lib\\site-packages\\numpy\\core\\include\\numpy\\arrayobject.h", | |
| "C:\\Users\\builder\\Miniconda2\\envs\\crick\\lib\\site-packages\\numpy\\core\\include\\numpy\\npy_math.h", | |
| "C:\\Users\\builder\\Miniconda2\\envs\\crick\\lib\\site-packages\\numpy\\core\\include\\numpy\\ufuncobject.h", | |
| "crick\\tdigest_stubs.c" |
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| import os | |
| import graphviz | |
| from dask.optimize import key_split | |
| from dask.dot import _get_display_cls | |
| from dask.core import get_dependencies | |
| def node_key(s): | |
| if isinstance(s, tuple): |
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| from __future__ import division, print_function | |
| from time import time | |
| import numpy as np | |
| from sklearn.datasets import fetch_covtype | |
| from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier | |
| from sklearn.metrics import zero_one_loss | |
| from sklearn.utils import check_array |
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| import platform | |
| import ctypes | |
| print("Implementation: %s" % platform.python_implementation()) | |
| def cell_set(cell, target): | |
| offset = 2 if platform.python_implementation() == 'PyPy' else 4 | |
| def inner(): |
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| import argparse | |
| from timeit import default_timer | |
| from collections import namedtuple | |
| import numpy as np | |
| import dask.array as da | |
| from dask.threaded import get | |
| from scipy.special import erf | |
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| _cache = {} | |
| def case(x): | |
| if x not in _cache: | |
| _cache[x] = type("Case", (Exception,), {}) | |
| return _cache[x] | |
| def switch(x): |