我正在研究语音数据的异常检测。我用 LSTM 编写的原始代码，但我面临着不平衡的数据集。所以我想从Pyod那里得到一些见解。
在尝试使用 Pyod 采样数据时，我只是将他们的代码复制并粘贴到我的 colab 中，但我遇到了错误，因为“ValueError：’c’ 参数有 1000 个元素，这与大小为 500 的 ‘x’ 和 ‘y’ 不一致。”

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pyod.utils.data import generate_data
contamination = 0.1 # percentage of outliers 10%
n_train = 500       # number of training points
n_test = 500        # number of testing points
n_features = 2      # number of features
X_train, y_train, X_test, y_test = generate_data(
 n_train=n_train, n_test=n_test, n_features= n_features, contamination=contamination)

# Make the 2d numpy array a pandas dataframe for each manipulation 
X_train_pd = pd.DataFrame(X_train)
# print(X_train_pd) 
# print(y_train) 

# Plot
plt.scatter(X_train_pd[0], X_train_pd[1], c=y_train, alpha=0.8)
plt.title('Scatter plot pythonspot.com')
plt.xlabel('x')
plt.ylabel('y')
plt.show()