Running Example Dataset - DiRo2C

Dataset diro2c_running_example_dataset.csv:

Two-dimensional dataset with the continuous features x1 and x2. It contains 300 instances with the following properties: min = − 293.39, max = 437.35, µ = − 2.92, and σ = 187.69 for feature x1 and min = − 251.96, max = 316.10, µ = − 3.23, and σ = 101.08 for feature x2. The instances of the datasets are classified into two classes “0” and “1”. The instances are generated by the sklearn “make_classification” function with the following parameters: make_classification(n_samples = 300, n_features = 2, n_informative = 1, n_redundant = 0, n_classes = 2, random_state = 2, n_clusters_per_class = 1, class_sep = 1.8, flip_y = 0, scale = 100).

数据集diro2c_running_example_dataset.csv：该数据集为包含连续特征x₁与x₂的二维数据集，共计300条样本。其中特征x₁的统计属性如下：最小值−293.39、最大值437.35、均值μ=−2.92、标准差σ=187.69；特征x₂的统计属性为：最小值−251.96、最大值316.10、均值μ=−3.23、标准差σ=101.08。该数据集的样本被划分为"0"与"1"两个类别，所有样本均通过sklearn的`make_classification`函数生成，所用参数为：n_samples=300、n_features=2、n_informative=1、n_redundant=0、n_classes=2、random_state=2、n_clusters_per_class=1、class_sep=1.8、flip_y=0、scale=100。