基于模型平均值的项目内部和跨项目缺陷预测
Tong Li1, Zhong Wang2, Peibei Shi1
1School of Computer and Artificial Intelligence, Hefei Normal University, No. 1688 Jinxiu Avenue, Hefei, 230601, Anhui, China.
Scientific reports
|February 21, 2025
概括
本研究介绍了一种用于软件缺陷预测的模型平均化技术. 与现有的算法相比,这种方法提高了项目内部和跨项目缺陷检测的准确性.
科学领域:
- 计算机科学 计算机科学
- 软件工程 软件工程 软件工程
背景情况:
- 软件缺陷预测对经济和金融部门至关重要.
- 早期识别有缺陷的软件模块非常重要.
研究的目的:
- 提出一个新的项目内部和跨项目软件缺陷预测技术.
- 使用模型平均理论来提高预测性能.
主要方法:
- 使用XGBoost和LightGBM作为候选机器学习模型.
- 通过确定权重来降低预测错误的应用模型平均值.
- 在四个公共数据集 (NASA,AEEEM,ReLink,SoftLab) 上使用交叉验证评估性能.
主要成果:
- 模型平均显示,在项目内预测方面,比XGBoost和LightGBM略有改进的结果.
- 在大多数项目内部场景中,超过了七个传统的机器学习算法.
- 与跨项目预测中的四种基准方法相比,在总体上表现优越.
结论:
- 拟议的模型平均方法实现了强大而准确的软件缺陷预测.
- 这种方法对于项目内部和跨项目缺陷预测任务都是有效的.
相关概念视频
01:03Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
01:25Multiple Regression
2.9K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.9K
01:19Variation
6.7K
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard deviation, which is the square root of variance.
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...
6.7K
01:13Mean Absolute Deviation
2.6K
The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
2.6K
01:11Regression Analysis
5.5K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.5K