Machine learning algorithm-oriented prediction and training process unification method and device
A machine learning and algorithm technology, applied in the computer field, can solve difficult problems such as the unification of the algorithm training process and the prediction process
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Embodiment 1
[0054] In order to facilitate the understanding of the unified method for the prediction and training process of the machine learning algorithm, this embodiment first introduces the machine learning algorithm.
[0055] The machine learning algorithm in this embodiment refers to a dynamic privacy protection machine learning algorithm, such as XGBoost (eXtreme Gradient Boosting, extreme gradient boosting) algorithm, GBDT (Gradient Boosting Decision Tree, gradient boosting decision tree) algorithm, LightGBM algorithm. Unless otherwise specified, the embodiments of the present disclosure use the XGBoost algorithm as an example of a dynamic privacy protection machine learning algorithm.
[0056] For the dynamic privacy-preserving machine learning algorithm, the object of the training process is a tensor structure, which can be easily indexed and easily generated. The object refers to the test_data and apply_data executed by different parties. The dynamic privacy protection machine ...
Embodiment 2
[0085] refer to image 3 , the embodiment of the present disclosure provides a unified device for the prediction and training process of machine learning algorithms, including:
[0086] The algorithm obtaining module 302 is used to obtain the first machine learning algorithm; wherein, the action object of the basic primitive in the first machine learning algorithm is a tree structure that cannot be accessed by indexing;
[0087] The primitive transformation module 304 is used for transforming the calculation flow of the basic primitive, so that the effect object of the basic primitive after transformation is a tree structure accessed in an index manner;
[0088] Algorithm conversion module 306, configured to convert the first machine learning algorithm into a second machine learning algorithm that meets the data privacy protection protocol based on the transformed basic primitives; wherein, the object of the second machine learning algorithm is accessed in an index manner A t...
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