title: ValueError: X has 1709 features per sample; expecting 2444
body: <p>I am using this code:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  from nltk.tokenize import word_tokenize
  import re
  </code></pre>
  
  <p>Using TFIDF vectorization</p>
  
  <pre><code>from sklearn.feature_extraction.text import TfidfVectorizer
  tv=TfidfVectorizer(max_df=0.5,min_df=2,stop_words='english')
  </code></pre>
  
  <p>Loading data files</p>
  
  <pre><code>df=pd.read_json('train.json',orient='columns')
  test_df=pd.read_json('test.json',orient='columns')
  
  df['seperated_ingredients'] = df['ingredients'].apply(','.join)
  test_df['seperated_ingredients'] = test_df['ingredients'].apply(','.join)
  
  df['seperated_ingredients']=df['seperated_ingredients'].str.lower()
  test_df['seperated_ingredients']=test_df['seperated_ingredients'].str.lower()
  
  cuisines={'thai':0,'vietnamese':1,'spanish':2,'southern_us':3,'russian':4,'moroccan':5,'mexican':6,'korean':7,'japanese':8,'jamaican':9,'italian':10,'irish':11,'indian':12,'greek':13,'french':14,'filipino':15,'chinese':16,'cajun_creole':17,'british':18,'brazilian':19 }
  df.cuisine= [cuisines[item] for item in df.cuisine]
  </code></pre>
  
  <p>Doing preprocessing</p>
  
  <pre><code>ho=df['seperated_ingredients']
  ho=ho.replace(r'#([^\s]+)', r'\1', regex=True)
  ho=ho.replace('\'"',regex=True)
  
  ho=tv.fit_transform(ho)
  
  from sklearn.model_selection import train_test_split
  X_train, X_test, y_train, y_test = train_test_split(ho,df['cuisine'],random_state=0)
  
  
  from sklearn.linear_model import LogisticRegression
  clf= LogisticRegression(penalty='l1')
  clf.fit(X_train, y_train)
  clf.score(X_test,y_test)
  
  from sklearn.linear_model import LogisticRegression
  clf1= LogisticRegression(penalty='l1')
  clf1.fit(ho,df['cuisine'])
  
  hs=test_df['seperated_ingredients']
  
  hs=hs.replace(r'#([^\s]+)', r'\1', regex=True)
  hs=hs.replace('\'"',regex=True)
  hs=tv.fit_transform(hs)
  
  ss=clf1.predict(hs) # this line is giving error.
  </code></pre>
  
  <p>Getting the above mentioned error while predicting. Does anyone know what I am doing wrong?</p>