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# IMPORTING PACKAGES
%pylab inline
%matplotlib inline
#from ggplot import *
from functools import partial
import os
import pandas as pd
import numpy as np
import scipy as sp
import statsmodels.api as sm
from string import letters
import copy
from sklearn.cross_validation import KFold, train_test_split, cross_val_score
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.datasets import make_classification
from sklearn.decomposition import PCA
from sklearn.metrics import roc_curve, auc, precision_recall_fscore_support
from sklearn import grid_search
from sklearn.preprocessing import LabelEncoder
from sklearn.ensemble import BaggingClassifier, AdaBoostClassifier, RandomForestClassifier, AdaBoostClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score, precision_recall_curve
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.base import clone
from sklearn.naive_bayes import GaussianNB
from sklearn.pipeline import Pipeline
from itertools import combinations
import matplotlib.pyplot as plt
from matplotlib.pylab import rcParams
rcParams['figure.figsize'] = 12, 4
#import seaborn as sns
#sns.set_context('talk')
#sns.set_style('whitegrid')
from dateutil.parser import parse
import itertools
from sklearn.metrics import confusion_matrix
from scipy.optimize import fmin
from scipy.optimize import curve_fit
import pylab as pl
from matplotlib import gridspec
# This is the 3D plotting toolkit
from mpl_toolkits.mplot3d import Axes3D
from sklearn.preprocessing import Normalizer