基础特征提取

Python 中的 NLP 特征工程

Rounak Banik

Data Scientist

字符数

"I don't know." # 13 characters
# Compute the number of characters 
text = "I don't know."
num_char = len(text)

# Print the number of characters
print(num_char)
13
# Create a 'num_chars' feature
df['num_chars'] = df['review'].apply(len)
Python 中的 NLP 特征工程

词数

# Split the string into words
text = "Mary had a little lamb."
words = text.split()

# Print the list containing words
print(words)
['Mary', 'had', 'a', 'little', 'lamb.']
# Print number of words
print(len(words))
5
Python 中的 NLP 特征工程

词数

# Function that returns number of words in string
def word_count(string):
    # Split the string into words
    words = string.split()

    # Return length of words list
    return len(words)
# Create num_words feature in df
df['num_words'] = df['review'].apply(word_count)

Python 中的 NLP 特征工程

平均词长

#Function that returns average word length
def avg_word_length(x):

# Split the string into words words = x.split()
# Compute length of each word and store in a separate list word_lengths = [len(word) for word in words]
# Compute average word length avg_word_length = sum(word_lengths)/len(words)
# Return average word length return(avg_word_length)
Python 中的 NLP 特征工程

平均词长

# Create a new feature avg_word_length
df['avg_word_length'] = df['review'].apply(doc_density)
Python 中的 NLP 特征工程

特殊特征

 

Datacamp 推文

Python 中的 NLP 特征工程

话题标签与提及

# Function that returns number of hashtags
def hashtag_count(string):

# Split the string into words words = string.split()
# Create a list of hashtags hashtags = [word for word in words if word.startswith('#')]
# Return number of hashtags return len(hashtags)
hashtag_count("@janedoe This is my first tweet! #FirstTweet #Happy")
2
Python 中的 NLP 特征工程

其他特征

  • 句子数
  • 段落数
  • 以大写字母开头的词
  • 全大写词
  • 数值数量
Python 中的 NLP 特征工程

Passons à la pratique !

Python 中的 NLP 特征工程

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