Question

我试图从大型数据框中找出最佳功能。我可以获取压缩的数据帧值，但无法获取所选功能的名称。下面是我的代码：

print('Shape of the bigramdf before feature selection:',bigram_df.shape)
if not os.path.isfile('smalldata/bigram_feather_top_100.feather'):
    SelectKBest(score_func=chi2,k=100).fit(bigram_df.iloc[:,:-1],df['class'])
    cols=SelectKBest.get_support(indices=False) # I am getting error here
    selc_k_best_byte_bigram=bigram_df[:,cols]
    selc_k_best_byte_bigram['id']=bigram_df['id']
    selc_k_best_byte_bigram.to_feather('smalldata/bigram_feather_top_100.feather')

    print('Shape of the bigramdf before feature selection:',selc_k_best_byte_bigram.shape)
else:
    selc_k_best_byte_bigram=pd.read_feather('smalldata/bigram_feather_top_100.feather')

我遇到以下错误：

TypeError: get_support() missing 1 required positional argument: 'self'

有人可以帮助我找到为什么我收到此TypeError

Answer 1

我认为您需要在变量中初始化类，然后调用.get_support。因此，请尝试替换：

SelectKBest(score_func=chi2,k=100).fit(bigram_df.iloc[:,:-1],df['class'])

与

k_best = SelectKBest(score_func=chi2,k=100).fit(bigram_df.iloc[:,:-1],df['class'])
cols = k_best.get_support(indices=False)

选择K个最佳功能

1 个答案: