AI决策树算法(C++ 11)
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#include <iostream>

// 定义一个决策树节点
struct TreeNode {
std::string value;
TreeNode* left;
TreeNode* right;

TreeNode(std::string val) {
value = val;
left = nullptr;
right = nullptr;
}
};

// 决策树的预测函数
std::string predict(TreeNode* root, std::string input) {
if (root == nullptr) {
return "";
}

if (root->left == nullptr && root->right == nullptr) {
return root->value;
}

std::string feature = root->value;
if (input == feature) {
return predict(root->left, input);
} else {
return predict(root->right, input);
}
}

int main() {
// 构建一个简单的决策树
TreeNode* root = new TreeNode("Outlook");
root->left = new TreeNode("Sunny");
root->right = new TreeNode("Rainy");
root->left->left = new TreeNode("Hot");
root->left->right = new TreeNode("Cool");
root->right->left = new TreeNode("Windy");
root->right->right = new TreeNode("Humid");

// 输入一个特征,预测结果
std::string input = "Sunny";
std::string result = predict(root, input);
std::cout << "预测结果: " << result << std::endl;

// 释放内存
delete root->left->left;
delete root->left->right;
delete root->right->left;
delete root->right->right;
delete root->left;
delete root->right;
delete root;

return 0;
}
使用tensorflow库来实现一个简单的神经网络模型的训练和预测
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#include <iostream>
#include <tensorflow/c/c_api.h>

int main() {
// 创建一个tensorflow会话
TF_SessionOptions* session_options = TF_NewSessionOptions();
TF_Session* session = TF_NewSession(session_options, tf_status);

// 加载模型
TF_Graph* graph = TF_NewGraph();
TF_Status* status = TF_NewStatus();
const char* model_path = "model.pb";
TF_Buffer* graph_def = read_model_from_file(model_path);
TF_ImportGraphDefOptions* import_options = TF_NewImportGraphDefOptions();
TF_GraphImportGraphDef(graph, graph_def, import_options, status);
TF_DeleteBuffer(graph_def);
TF_DeleteImportGraphDefOptions(import_options);

// 创建输入tensor和输出tensor
TF_Output input_op = {TF_GraphOperationByName(graph, "input"), 0};
TF_Output output_op = {TF_GraphOperationByName(graph, "output"), 0};
TF_Tensor* input_tensor = create_input_tensor();

// 运行模型
TF_Tensor* output_tensor = nullptr;
TF_SessionRun(session, nullptr, &input_op, &input_tensor, 1, &output_op, &output_tensor, 1, nullptr, 0, nullptr, status);

// 处理输出结果
float* output_data = static_cast<float*>(TF_TensorData(output_tensor));
std::cout << "预测结果: " << output_data[0] << std::endl;

// 释放资源
TF_DeleteTensor(input_tensor);
TF_DeleteTensor(output_tensor);
TF_DeleteStatus(status);
TF_DeleteGraph(graph);
TF_CloseSession(session, status);
TF_DeleteSession(session, status);
TF_DeleteSessionOptions(session_options);

return 0;
}

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