puraminy

from sklearn.decomposition import PCA
import scipy.io as sio
import matplotlib.image as image
import matplotlib.image as mpimg
import pandas as pd
import matplotlib.pyplot as plt
import cv2
import numpy as np
import math
import operator

puraminy

from sklearn.decomposition import PCA
import scipy.io as sio
import matplotlib.image as image
import matplotlib.image as mpimg
import pandas as pd
import matplotlib.pyplot as plt
import cv2
import numpy as np
import math
import operator

puraminy

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from numpy import array
from numpy import mean
from numpy import cov
from numpy.linalg import eig, svd

puraminy

import nltk, re, pprint
from nltk import word_tokenize
import numpy as np
import pandas as pd
import heapq
import string 

from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import LogisticRegression

puraminy

import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn import preprocessing
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neighbors import RadiusNeighborsClassifier
from sklearn.naive_bayes import GaussianNB
import matplotlib.pyplot as plt

puraminy

import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn import preprocessing
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neighbors import RadiusNeighborsClassifier
from sklearn.naive_bayes import GaussianNB
import matplotlib.pyplot as plt

puraminy

import numpy as np
import pandas as pd
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn import preprocessing
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neighbors import RadiusNeighborsClassifier
from sklearn.naive_bayes import GaussianNB
import matplotlib.pyplot as plt

puraminy

import numpy as np
from sklearn import preprocessing
from sklearn.metrics import accuracy_score
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
import itertools
import seaborn as sn
from sklearn.metrics import confusion_matrix, classification_report, accuracy_score, f1_score
import matplotlib.pyplot as plt

puraminy

import numpy as np
from scipy.stats import multivariate_normal
from sklearn.feature_selection import VarianceThreshold
from sklearn.metrics import accuracy_score
import seaborn as sn
from sklearn.metrics import confusion_matrix, classification_report, accuracy_score, f1_score
import matplotlib.pyplot as plt
from sklearn import preprocessing

puraminy

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import networkx as nx


df = pd.DataFrame(np.zeros((5,14)), columns = ['علی','مدرسه', 'را', 'دوست','دار',
                             'برای','او','زندان', 'است', 'کمی','در','درس','خوان', 'بازیگوش'])

s1 = 'علی مدرسه را دوست دار'