LT-FS-ID: Intrusion detection data WSNs

This dataset is consist of five columns. The first four columns represent the input features (i.e., area, sensing range, transmission range, and the number of sensors). The last column represents the response variable or target variable (i.e., number of barriers). Through this dataset, we can set up a regression model to predict the number of barriers required for fast intrusion detection and prevention in machine learning.本数据集共包含五列数据。前四列为输入特征，即覆盖区域、感知范围、传输范围与传感器数量。最后一列为响应变量（亦称目标变量），即障碍数量。借助本数据集，可构建回归模型，以预测快速入侵检测与防御所需的障碍数量，应用于机器学习任务中。