function [par,label]=training_data(Arc) [~,FrontNo,CrowdDis] = EnvironmentalSelection_NSGAII(Arc,size(Arc.objs,1)); t2=find(FrontNo(1,:)<=1); parpop=Arc.decs; parp=parpop(t2,:); t3=find(FrontNo(1,:)>1); parn=parpop(t3,:); par = [parp;parn]; label = 2*ones(size(par,1), 1); label(1:size(parp,1)) = 1; end

这段代码是用于生成训练数据的。它的输入参数是一组解集合 Arc，通过调用 EnvironmentalSelection_NSGAII 函数来对其进行非支配排序，从而得到每个解的前沿等信息。然后，根据前沿信息将解集分为两部分，一部分是前沿解集，另一部分是非前沿解集。最后，将这些解作为训练数据，并将前沿解标记为1，非前沿解标记为2。函数的输出是生成的训练数据 par 和对应的标签 label。

相关问题

sdata=sql_data() TypeError: 'module' object is not callable

This error occurs when you try to call a module as a function.

For example, if you have a module named "sql_data" and you try to call it as a function like this:

sdata = sql_data()

Python will raise a TypeError because "sql_data" is not a function, it is a module.

To fix this error, you need to check if you are calling a module or a function. If you want to use a function from the module, you need to import it first and then call the function using the module name and function name separated by a dot.

For example:

from sql_data import my_function
sdata = my_function()

This will import the "my_function" function from the "sql_data" module and call it.

image_to_label = image_logits.argmax(dim=1)

This code snippet is using PyTorch to convert the logits (output of a neural network) from an image classification model into class labels.

The `argmax` function returns the index of the maximum element along a specified dimension (in this case, `dim=1`, which corresponds to the class dimension). So `image_logits.argmax(dim=1)` returns a tensor of the same shape as `image_logits`, but with each element replaced by its corresponding class label (the index of the class with the highest probability).

This is useful for evaluating the performance of the model on a dataset with known labels, and for predicting the class of new images.