MATLAB实现树数据结构的类封装

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在计算机科学和编程领域,树形数据结构是一种重要的数据结构,通常用于表示具有层次关系的数据。树形结构由节点组成,每个节点包含数据和指向其子节点的指针。在MATLAB环境下,此类可以为树形数据结构提供面向对象的封装,方便用户创建和操作树形结构。 MATLAB是一种高性能的数值计算和可视化环境,广泛用于工程、科学和数学领域中的算法开发、数据可视化、数据分析和数值计算。MATLAB提供了丰富的函数库,支持矩阵运算、函数和数据绘图、算法实现以及创建用户界面等功能。 在本资源中,用户可以找到实现树形结构的MATLAB类的源代码,该类可能包含树的创建、遍历、节点插入、节点删除等基本操作的方法。树的遍历算法可能包括深度优先搜索(DFS)和广度优先搜索(BFS)。深度优先搜索通常使用递归或栈来实现,而广度优先搜索则使用队列。此外,该类可能还提供了访问和修改节点数据的接口,以及对树结构进行排序、剪枝等高级操作的能力。 文件名称列表中的'新建文本文档.txt'可能包含有关该MATLAB类的使用说明、示例代码或文档。而'matlab-tree-master'文件夹中应当包含该类的源代码文件以及其他必要的文件,例如单元测试文件、帮助文件或配置文件。用户可以使用MATLAB的类编辑器来查看、编辑和扩展这些类的功能。 需要注意的是,由于压缩文件的名称中没有提供具体的标签,我们无法从中获取特定于实现细节的信息,例如树的具体类型(比如二叉树、红黑树等),或是该类是否支持特定的树操作算法。因此,此处提供的信息主要基于对树形数据结构及MATLAB编程环境的一般性描述。"

Create a class called Rational for performing arithmetic with fractions. Use integer variables to represent the private data of the class – the numerator and the denominator. Provide a constructor that enables an object of this class to be initialized when it’s declared. The constructor should store the fraction in reduced form. For example, the fraction 2/4 would be stored in the object as 1 in the numerator and 2 in the denominator. In order to compute the reduced form, you need to write a reduction function which uses the Euclidean algorithm to get the greatest common divisor (GCD) of the numerator and denominator first and then divides GCD to get the reduced numerator and denominator. Provide public member functions that perform each of the following tasks: (a) Subtract a Rational number from the other Rational number. The result should be stored in reduced form. (b) Divide a Rational number by the other Rational number. The result should be stored in reduced form. (c) Print Rational numbers in the form a/b, where a is the numerator and b is the denominator. (d)Compare two Rational numbers to make sure which one is smaller or they are equal. (1 for the first number, 2 for the second number and 0 if they are equal) Please also write a main function to prompt the user to input two Rational numbers . Subtract one number from the other from these two numbers using (a) and then print the result using (c). Divide one number from the other from these two numbers using (b) and then print the result using (c). Compare these two Rational numbers using (d) and indicate which one is smaller or they are equal. 用c++5.11寫出,且使用using namespace std;

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I am an AI language model and cannot create images directly. However, I can describe the structure of the DeepNeuralNet class in a text format, which you can use as a guide to drawing the network structure. The structure looks like this: 1. Input Layer: This is where the network receives user and item inputs. Each input goes through an embedding layer, with n_users and n_items as the number of embeddings, and n_factors as the size of the embeddings. 2. Concatenation Layer: The output of the user and item embedding layers is concatenated, resulting in a tensor of shape (batch_size, n_factors*2). 3. Fully Connected Hidden Layers: The concatenated tensor is then passed through a series of fully connected layers. In your case, you have two hidden layers of sizes 64 and 32. Each layer is defined as a Linear layer with a specified number of input and output features, and these layers are stored in a ModuleList (fc_layers). 4. Dropout Layer: After passing through the hidden layers, the network goes through a dropout layer with probability 0.2. This randomly sets some elements to zero during training to prevent overfitting. 5. Output Layer: After the dropout layer, the network passes through another Linear layer, which reduces the tensor's dimension to 1. 6. Sigmoid Activation: Finally, the output goes through a sigmoid activation function, which squashes the output value between 0 and 1. The sigmoid activation is applied to make the output ready for predicting ratings or binary outcomes such as preferences. To draw the structure, you can use rectangles to represent the Linear layers and circles for activation functions. Label the rectangles with the number of input and output features, and label the circles with the activation function's name. Connect the rectangles with lines to visualize the information flow.用图展示这个网络层·

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