Jupyter Notebook 中 'out' 的含义：训练数据分割和返回值

在 Jupyter Notebook 中，'out' 指的是函数的返回值。该代码段执行后会返回 x_train, y_train, x_val, y_val, x_test, y_test['RemainingUsefulLife'] 这些变量的值。

这段代码主要用于进行训练数据分割，并返回训练集、验证集和测试集数据。

代码分析:

# train-val split
    gss = GroupShuffleSplit(n_splits=1, train_size=0.80, random_state=42)
    # generate the train/val for *each* sample -> for that we iterate over the train and val units we want
    # this is a for that iterates only once and in that iterations at the same time iterates over all the values we want,
    # i.e. train_unit and val_unit are not a single value but a set of training/vali units
    for train_unit, val_unit in gss.split(X_train_pre['unit_nr'].unique(), groups=X_train_pre['unit_nr'].unique()): 
        train_unit = X_train_pre['unit_nr'].unique()[train_unit]  # gss returns indexes and index starts at 1
        val_unit = X_train_pre['unit_nr'].unique()[val_unit]

        x_train = gen_data_wrapper(X_train_pre, sequence_length, sensors, train_unit)
        y_train = gen_label_wrapper(X_train_pre, sequence_length, ['RUL'], train_unit)
        
        x_val = gen_data_wrapper(X_train_pre, sequence_length, sensors, val_unit)
        y_val = gen_label_wrapper(X_train_pre, sequence_length, ['RUL'], val_unit)

    # create sequences for test 
    test_gen = (list(gen_test_data(X_test_pre[X_test_pre['unit_nr']==unit_nr], sequence_length, sensors, -99.))
                for unit_nr in X_test_pre['unit_nr'].unique())
    x_test = np.concatenate(list(test_gen)).astype(np.float32)
    
    return x_train, y_train, x_val, y_val, x_test, y_test['RemainingUsefulLife']

    # exponential smoothing
    X_train_pre= exponential_smoothing(X_train_pre, sensors, 0, alpha)
    X_test_pre = exponential_smoothing(X_test_pre, sensors, 0, alpha)

首先使用 GroupShuffleSplit 分割数据，将数据集分为训练集和验证集。
然后通过 gen_data_wrapper 和 gen_label_wrapper 函数生成训练集和验证集的数据和标签。
最后使用 gen_test_data 函数生成测试集数据。

返回值:

x_train: 训练集数据
y_train: 训练集标签
x_val: 验证集数据
y_val: 验证集标签
x_test: 测试集数据
y_test['RemainingUsefulLife']: 测试集标签中的 'RemainingUsefulLife' 特征

总结:

'out' 指的是函数的返回值，通常用于保存代码执行后的结果。
这段代码示例展示了如何进行训练数据分割和返回值，以及如何使用返回值进行后续操作。