Sample generation and survival evaluation method and device based on data genetic variation
A genetic variation and sample technology, applied in the computer field, can solve problems such as lack of samples, only a small number of samples, and difficulty in machine learning to build models, and achieve high consistency results
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Embodiment 1
[0057] Such as figure 1 As shown, on the one hand, the present invention provides a method for sample generation and survival assessment based on genetic variation of data, which may specifically include the following steps:
[0058] S101. Parental sample preparation: According to the business scenario, the initial parental sample is obtained, the time window of the initial parental sample is T1, and the feature space is Xi (i is the dimension of the feature vector, usually a high-dimensional vector). The labels of the initial parental samples are classified into three categories, positive, negative, and indeterminate. The total amount of initial parental samples is D1, among which the positive sample is Dp, the negative sample is Dn, and the uncertain sample is Du, obviously Dp+Dn+Du=D1.
[0059] S102. Parental crossover: combining various initial parental samples, and crossover to obtain labels of offspring samples. There are many specific crossing schemes, such as: positi...
Embodiment 2
[0071] Another aspect of the present invention also provides a device for implementing the above-mentioned sample generation and survival assessment method based on genetic variation of data, please refer to figure 2 , the device includes:
[0072] Business data storage module: used to accept and store business data, and provide initial parent samples;
[0073] Massive sample generation module: used to accept the initial parental samples, cooperate with the parameters and rules provided by the rule configuration module, and generate massive sub-generational samples;
[0074] Rule configuration module: used to visually configure genetic coefficients, coefficients of variation, and static survival rules;
[0075] Survival model operation module: used for training and deploying multiple survival model classifiers, used for static and dynamic generation and evaluation of offspring samples, and output sample survival results and corresponding survival weights;
[0076] Sample re...
Embodiment 3
[0080] Another aspect of the present invention also provides a computer device, such as image 3 As shown, the computer device includes a memory, a processor, a communication interface, and a communication bus, and a computer program that can run on the processor is stored in the memory, and when the processor executes the computer program, the methods in the above-mentioned embodiments are implemented. step.
[0081] The processor may be a central processing unit (Central Processing Unit, CPU).
[0082] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs, non-transitory computer-executable programs and units, such as the corresponding program units in the above method embodiments of the present invention. The processor runs the non-transitory software programs, instructions and modules stored in the memory to execute various functional applications of the processor and process data of works, that is, to reali...
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