Random grouping method and device, computer equipment and storage medium
A grouping method and technology of the control group, applied in the field of data statistics, can solve problems such as inability to directly calculate numerical variables, affect the accuracy of experimental results, and lose information on numerical variables, so as to avoid information loss, ensure accuracy, and distribute between groups minimal difference in effect
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Embodiment 1
[0043] This embodiment provides a random grouping method, figure 1It is a flowchart illustrating that according to some embodiments of the present invention, the samples to be grouped are calculated to obtain the comprehensive evaluation index value, and the samples to be grouped are divided into the most suitable treatment groups according to the result of the comprehensive evaluation index value. Although the processes described below include operations in a particular order, it should be clearly understood that these processes may also include more or fewer operations, which may be performed sequentially or in parallel (e.g., using parallel processors) or multi-threaded environment).
[0044] This embodiment provides a random grouping method for dividing samples to be grouped into corresponding treatment groups, avoiding information loss caused by converting numerical variables into categorical variables, and ultimately affecting the accuracy of experimental results. Such ...
Embodiment 2
[0113] This embodiment provides a random grouping device, which is used to divide the samples to be grouped into corresponding treatment groups, avoiding information loss caused by converting numerical variables into categorical variables, and ultimately affecting the accuracy of experimental results. Such as figure 2 shown, including:
[0114] The acquisition module 201 is configured to acquire samples to be grouped, and the samples to be grouped are index values measured by clinical trials. For details, please refer to the relevant description of step S101 in Embodiment 1, which will not be repeated here.
[0115] Calculation module 202, used to sequentially calculate the comprehensive evaluation obtained by adding the samples to be grouped into each treatment group according to the number of treatment groups, the data in each treatment group, the weight of the category corresponding to the samples to be grouped, and the number of categories Index value. For details, p...
Embodiment 3
[0127] This embodiment provides a computer device, such as image 3 As shown, the device includes a processor 301 and a memory 302, wherein the processor 301 and the memory 302 can be connected through a bus or in other ways, image 3 Take connection via bus as an example.
[0128]The processor 301 may be a central processing unit (Central Processing Unit, CPU). The processor 301 may also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), graphics processors (Graphics Processing Unit, GPU), embedded neural network processors (Neural-network Processing Unit, NPU) or other Dedicated deep learning coprocessor, application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components and other chips, or a combination of the above-mentioned types ...
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