1. Determine the experimental goal: First, you need to define your experimental goal. This may be to verify whether your algorithm is more effective than existing algorithms or to evaluate the performance of your model under different conditions.
2. Choose a data set: Choose a data set suitable for your experimental goal. This data set should contain enough samples so that you can make meaningful statistical analysis. At the same time, the data set should represent your actual application scenario, so that your experimental results have practical application value.
3. Design the experiment: design your experimental scheme. This may include selecting appropriate evaluation indexes, determining the parameters of the experiment and designing the running order of the experiment.
4. Experiment: Experiment according to your experiment plan. In this process, you need to record all the experimental results for subsequent analysis.
5. Analysis results: Analyze the experimental results. This may include calculating evaluation indicators, drawing performance curves, and making statistical analysis.
6. Explain the results: According to your experimental results, explain the performance of your algorithm or model. This may include explaining why your algorithm or model works well in some cases and in which cases it may need to be improved.
7. Write the experiment part: Finally, write your experiment process and results into your paper. This part should describe your experimental method in detail and clearly, as well as your experimental results and analysis.
The above are some basic steps for the experimental verification of the paper data set. It should be noted that experimental verification is an iterative process, and you may need to adjust your experimental scheme and parameter settings several times to get the best experimental results.