nmayorov

nmayorov

import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import load_diabetes, load_boston
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import cross_val_score
from sklearn.feature_selection import (SelectKBest, MutualInfoSelector,
                                       f_classif, f_regression)
from sklearn.pipeline import make_pipeline

nmayorov

import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import load_digits
from sklearn.feature_selection import RFE, MutualInfoSelector
from sklearn.preprocessing import minmax_scale
from sklearn.svm import LinearSVC
from sklearn.model_selection import cross_val_score

digits = load_digits()
X = minmax_scale(digits.data)

nmayorov

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from sklearn.preprocessing import Imputer
from sklearn.feature_selection import (
    SelectKBest, MutualInfoSelector, f_regression)
from sklearn.linear_model import RidgeCV
from sklearn.model_selection import cross_val_score

data = pd.read_csv('communities.data', header=None)

nmayorov

from decimal import Decimal, getcontext
import numpy as np
from math import isfinite


EPS = np.finfo(float).eps


class ComplexDecimal(object):
    def __init__(self, real, imag):

nmayorov

nmayorov

nmayorov

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nmayorov

from __future__ import division, absolute_import, print_function

import inspect

import numpy as np

from numpy.testing import assert_, assert_allclose
from scipy import linalg, interpolate, special
from scipy.integrate import solve_bvp