You can combine two trained semi-supervised algorithms using various methods. Here are some examples of how to implement these methods:
- Majority Voting
graph_output = graph_based_algorithm(test_data);
svm_output = svm_algorithm(test_data);
% Combine the outputs using majority voting
ensemble_output = mode([graph_output, svm_output], 2);
2. Model stacking
graph_features = graph_based_algorithm(data);
svm_output = svm_algorithm(graph_features);
Note that these are just examples, and the exact implementation will depend on the specific characteristics of your algorithms and data.
Similarly, you can experiment with different ensemble methods and see what works best for your use case.
