chkoar

Keybase proof

I hereby claim:

• I am chkoar on github.
• I am chkoar (https://keybase.io/chkoar) on keybase.
• I have a public key ASAbSg2GwCBc-h7NJdDMAFb7ak2LQoMFgacgQZQFSZQfDgo

To claim this, I am signing this object:

chkoar

import numpy as np
from imblearn.over_sampling import SMOTE


def generate_data(X, ratio=1.0, resampler=None, random_state=None):

    y = [1] * X.shape[0]

    n_samples = X.shape[0]
    n_features = X.shape[1]

chkoar

def uuid(seed=None):
    """
    Shortcut function to generate reproducible version 4 
    Universally Unique IDentifiers (UUIDs).
    """
    
    import uuid
    import random

    rd = random.Random()

chkoar

import pandas as pd

def describex(data):
    data = pd.DataFrame(data)
    stats = data.describe()
    skewness = data.skew()
    kurtosis = data.kurtosis()
    skewness_df = pd.DataFrame({'skewness':skewness}).T
    kurtosis_df = pd.DataFrame({'kurtosis':kurtosis}).T
    return stats.append([kurtosis_df,skewness_df])

chkoar

import uuid
from pathlib import Path

from sklearn.base import BaseEstimator, ClassifierMixin, clone
from sklearn.datasets import make_classification
from sklearn.externals import joblib
from sklearn.feature_selection import SelectPercentile
from sklearn.model_selection import cross_val_score
from sklearn.pipeline import make_pipeline
from sklearn.svm import LinearSVC

chkoar

def test_stationarity(timeseries):
    import matplotlib.pyplot as plt
    from statsmodels.tsa.stattools import adfuller
    
    #Determing rolling statistics
    rolmean = pd.rolling_mean(timeseries, window=12)
    rolstd = pd.rolling_std(timeseries, window=12)

    #Plot rolling statistics:
    orig = plt.plot(timeseries, color='blue',label='Original')

chkoar

import sys
from imblearn.combine import *
from imblearn.over_sampling import *
from imblearn.under_sampling import *

def make_sampler(cls, **kwargs):
    _ = sys.modules[__name__]
    return getattr(_, cls)().set_params(**kwargs)

# example