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我是scikit學習和numpy的新手。我怎麼能代表我的數據集由列表/字符串數組組成,例如列表/數組字符串到numpy浮點數組
[["aa bb","a","bbb","à"], [bb cc","c","ddd","à"], ["kkk","a","","a"]]
給一個numpy數組的dtype float?
我是scikit學習和numpy的新手。我怎麼能代表我的數據集由列表/字符串數組組成,例如列表/數組字符串到numpy浮點數組
[["aa bb","a","bbb","à"], [bb cc","c","ddd","à"], ["kkk","a","","a"]]
給一個numpy數組的dtype float?
我認爲你所尋找的是你的單詞的數字表示。您可以使用gensim並將每個單詞映射到令牌id,然後從中創建您的numpy陣列,如下所示:
import numpy as np
from gensim import corpora
toconvert = [["aa bb","a","bbb","à"], ["bb", "cc","c","ddd","à"], ["kkk","a","","a"]]
# convert your list of lists into token id's. For example, 'aa bb' could be represented as a 2, a as a 1, etc.
tdict = corpora.Dictionary(toconvert)
# given nested structure, you can append nested numpy arrays
newlist = []
for l in toconvert:
tmplist = []
for word in l:
# append to intermediate list the id for the given word under observation
tmplist.append(tdict.token2id[word])
# convert to numpy array and append to main list
newlist.append(np.array(tmplist).astype(float)) # type float
print(newlist) # desired output: [array([ 2., 0., 1., 0.]), array([ 5., 3., 4., 6., 0.]), array([ 7., 0., 8., 0.])]
# and to see what id's represent which strings:
tdict[0] # 'a'
感謝@datawrestler爲您提供的答案。這非常有用。 –
whaat ???將字符串轉換爲浮點數?順便說一下,它與sklearn無關 – MMF
好吧,也許我沒有使用正確的術語,但@datawrestler瞭解我的問題,並給出了一個非常有用的建議。不管怎麼說,還是要謝謝你。 –