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我正在为我的数据集运行 KNN，为此我必须估算缺失值，然后转换变量，使它们可以位于 0 和 1 之间。

我必须将此预测结果用作推断性能并为此制作 TTD 模型。

当我使用 predict 时，我可以获得预测的概率，但我无法将这些结果转移到基础数据集中，以便可以用来推断性能。

请在下面找到示例代码 -

train=pandas.read_csv("dev_in.csv")
y_train = train['Y']
w_train = train['WT']
x_train1 = train[[‘ABC’,’GEF’,’XYZ’]].replace(-1, numpy.NaN)
values = x_train1.values
imputer = Imputer()
#replacing with mean
x_train_trf = imputer.fit_transform(values) 
# count the number of NaN values in each column
print(numpy.isnan(x_train_trf).sum())
X_normalized = preprocessing.normalize(x_train_trf, norm='l2')

#similar data manipulations on test population
test=pandas.read_csv("oot_in.csv")
y_test = test['Y']
w_test = test['WT']
x_test1 = test[[‘ABC’,’GEF’,’XYZ’]].replace(-1, numpy.NaN)
print(numpy.isnan(x_test81).sum())
values_test = x_test1.values
imputer = Imputer()
#replacing with mean
x_test_trf = imputer.fit_transform(values_test) 
# count the number of NaN values in each column
print(numpy.isnan(x_test_trf).sum())
X_normalized_test = preprocessing.normalize(x_test_trf, norm='l2')

#fitting the KNN
knn = KNeighborsClassifier(n_neighbors=5, weights= 'distance', p=2)
knn.fit(X_normalized, y_train)

#checking prediction on the test population
y_pred_test = knn.predict(X_normalized_test) 
**test ['inferred'] = y_pred_test**
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-82-defc045e7eeb> in <module>()
----> 1 test ['inferred] = y_pred_test

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

我尝试创建在测试数据集中推断的变量的地方，我收到了上述错误。

对你的帮助表示感谢。

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