我已经用 box-Cox 转换转换了我的整个数据框（相关和独立），并且我有下面的数组作为系数：
array([-0.12050315, -0.07470903, -0.11079292, -0.22158582, -0.06629854,
-0.14941804, -0.11161256, -0.08786566, -0.17451716, -0.10773153,
-0.09787049, -0.19569526, -0.21546309, -0.12817391, -0.03621895,
-0.22004721, -0.10557047, -0.06584703, -0.13174353, 0.16621695,
0.01901815, -0.1635233 , 0.15919524, 0.05952151, 0.06084785,
0.01126627, 0.01126626, -0.87299313])
在训练我的 Keras 回归模型后，我想对测试目标（y_test）和预测值（y_pred）进行逆变换。我使用的代码来自 sklearn 包，如下所示：对于 y_test 如下：
array([ 0.98333783, 1.50200139, 1.83218911, -0.15996774, 0.78260773,
0.74395122, -1.03379222, -1.49198108, 1.15562537, 1.12287162,
-0.73178092, 1.81372947, -1.07406015, 0.33985499, 1.03716673,
-1.57230688, 1.47911475, 0.84982504, -1.44474193, -0.56389331,
-0.20603036, 0.1266229 , 0.34537935, -0.91948754, -0.0859256 ,
-1.04186052, -0.46334846, -0.60194859, 1.49238056, 0.05740751,
0.00789972, 1.72823035, -0.60434219, -1.53115573, 1.65947602,
1.55132413, -1.63633904, 1.50525545, -1.41644302, 1.18606998,
-0.97952481, 1.791517 , 0.74122464, 1.35466604, -0.91996944,
-0.66993356, -0.27276727, -0.70785461, 0.97178584, -0.26121448,
-1.38664819, 1.10732533, -1.41707219, 1.9831894 , -1.13688763,
0.8281032 , -0.21455527, -0.42318826, -0.10473893, -0.2152237 ,
-1.47820045, 0.94680937, -0.17741741, 0.63605613, -0.39629346,
1.09077037, -0.51547212, -0.67354063, -1.57748571, -0.79634151,
0.15821278, 0.46977151, 0.27850129, 0.07907392, -0.93708215,
1.53871748, -1.21563852, 0.79040892, 0.21197071, -0.66894071,
0.27635132, 1.28436786, 0.48883812, -0.05657853, 1.28865163,
-0.54660271, 1.11260471, -1.24212802, 1.71250636, 0.6430331 ,
0.71056295, 1.09364413, -0.43520344, -0.51681466, 0.54017086,
0.61223984, 0.05203929, 0.83618294, -0.55494482, -0.04054612,
-0.0886779 , 1.44277091, 1.77569744, 0.86381339, 0.15509978,
0.65514589, -0.39788517, -0.91833687, 0.42345815, -0.86787368,
0.20091955, 0.59593155, 1.69567572, 0.51849197, 0.60554069,
1.32229222, -1.57268445, -0.19908104, 0.04183203, -0.18814032,
-0.33261663, -0.2595337 , -0.74548164, 1.29234243, 1.52822498,
0.04565854, 2.08218297])
def inverse_bc(vector , lam):
if lam == 0:
inv = exp(vector)
else:
inv = ((np.sign(vector)*np.abs(vector) * lam) + 1) ** (1 / lam)
return inv
y_lambda = power.lambdas_[-1] #-0.87299313
inverse_bc(y_test , y_lambda)
我在返回的数组中得到了一些nan值，如下所示：
*array([0.10610358, nan, nan, 1.16152319, 0.26775244,
0.30072773, 2.08877834, 2.5988645 , nan, 0.0106793 ,
1.76078457, nan, 2.13303091, 0.66815944, 0.0666456 ,
2.68968613, nan, 0.2116487 , 2.54563854, 1.58165874,
1.20858382, 0.8744233 , 0.66291199, 1.96381267, 1.0863822 ,
2.09763562, 1.47558096, 1.62204719, nan, 0.94280366,
0.99210423, nan, 1.62459181, 2.6431087 , nan,
nan, 2.76236425, nan, 2.51382021, nan,
2.02932817, nan, 0.30307155, nan, 1.96433746,
1.69451594, 1.27717759, 1.7351098 , 0.11484951, 1.26526928,
2.48037479, 0.01982524, 2.51452707, nan, 2.20230692,
0.22959532, 1.21731914, 1.43347482, 1.10541436, 1.21800441,
2.58332304, 0.13404354, 1.17932312, 0.39511208, 1.40536365,
0.03020463, 1.53045691, 1.69837201, 2.69555511, 1.83029795,
0.84343459, 0.54620617, 0.72678135, 0.92132898, 1.98298456,
nan, 2.28953023, 0.26115763, 0.79103097, 1.69345474,
0.72884676, nan, 0.52857803, 1.0567779 , nan,
1.56335081, 0.01664213, 2.31896501, nan, 0.38891339,
0.32958372, 0.0283648 , 1.44605602, 1.53187367, 0.48149097,
0.41636353, 0.94813399, 0.22289834, 1.57218039, 1.0406489 ,
1.0891639 , nan, nan, 0.2001915 , 0.84648205,
0.37818144, 1.40702539, 1.96255967, 0.58932261, 1.90770871,
0.8017689 , 0.43099541, nan, 0.50130903, 0.42236631,
nan, 2.69011397, 1.20146886, 0.95827965, 1.19027816,
1.3390913 , 1.26353796, 1.77550785, nan, nan,
0.95447464, nan])
*
我的第一个问题是，转换是否应该为每列返回一个值作为 lambda？请帮助我了解这些 nan 值是什么？
谢谢