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我試圖對兩個類的分類問題執行維數降低。RuntimeWarning:在劃分S中遇到的無效值** 2))[:self._max_components]
我有6個csv文件。我的代碼在這裏:
def linear_discrimination_analysis(files):
with open(os.path.join("/Users", "byname", "PycharmProjects", "sensorLogProject", "Data", files[0]),
'rU') as my_file_0:
df1 = sd.sample_difference(my_file_0)
for f in files[1:len(files) - 2]:
with open(os.path.join("/Users", "myname", "PycharmProjects", "sensorLogProject", "Data", f),
'rU') as my_file_1:
df1.append(sd.sample_difference(my_file_1))
with open(os.path.join("/Users", "myname", "PycharmProjects", "sensorLogProject", "Data", files[len(files) - 2]),
'rU') as my_file_2:
df2 = sd.sample_difference(my_file_2)
with open(os.path.join("/Users", "myname", "PycharmProjects", "sensorLogProject", "Data", files[len(files) - 1]),
'rU') as my_file_3:
df2.append(sd.sample_difference(my_file_3))
X = df1[['x', 'y', 'z']].values
y = df2['label'].values
lda = LDA(n_components=1)
lda.fit_transform(X, y.ravel())
plt.show()
linear_discrimination_analysis(files)
我想這可能是問題所在。
這是我得到的錯誤:
每個文件都有行100的5列。我想使用第3,第4和第5列進行特徵提取,這些特徵提取稱爲'x','y'和'z'。
我明白了。那麼y應該是標籤呢? – dirtysocks45
那麼我應該如何設置培訓和測試套件? – dirtysocks45
當我將'y'改爲'y = [1,2]'(我有兩個類標籤)時,我現在得到'ValueError:找到輸入變量的樣本數不一致:[504,2]' – dirtysocks45