The paper investigates all (971) non-executed pending leading cases of the European Court of Human Rights (ECtHR) between 2012 and 2020 through Machine Learning (ML) techniques. Drawing on the extant scholarship, our interest on compliance has centred on state level and case level variables. For the identification of important variables, four databases have been used. Each country party to the European Convention on Human Rights (ECHR) received 232 distinct factors for eight years. Since we aim to make a parameter estimation for a high-dimensional data set, Simulated Annealing (SA) is employed as feature selection method. In the state level analysis, Support Vector Regression (SVR) model has been applied yielding the coefficients of the variables, which have been found to be important in spelling out non-compliance with the ECtHR decisions. For the case level analysis, different cluster techniques have been utilized and the countries have been grouped into four different clusters. We have found that the states that have relatively high levels of equality before the law, protection of individual liberties, social class equality with regard to enjoying civil liberties, access to justice and free and autonomous election management arrangements, are less susceptible to non-compliance of the decisions of the ECtHR. For the case level analysis, type of violated rights, the existence of dissent in the decision and dissenting votes of national judges for their appointing states affect the compliance behaviour of the states. In addition, a notable result of the research is that if a national judge casts a dissenting vote against the violation judgment of the ECtHR involving the state that appointed him/her, the judgment is likely not to be executed by the respondent state.

该论文通过机器学习（ML）技术调查了 2012 年至 2020 年间欧洲人权法院（ECtHR）所有（971 个）未执行的待决领先案件。借鉴现有的学术成果，我们对合规性的兴趣集中在州级和案例级变量上。为了识别重要变量，使用了四个数据库。八年来，《欧洲人权公约》(ECHR) 的每个缔约国都收到了 232 个不同的因素。由于我们的目标是对高维数据集进行参数估计，因此采用模拟退火（SA）作为特征选择方法。在州级分析中，应用了支持向量回归 (SVR) 模型来生成变量系数，人们发现这些系数对于阐明不遵守 ECtHR 决策的情况非常重要。对于案例级别分析，使用了不同的聚类技术，并将国家分为四个不同的聚类。我们发现，法律面前人人平等、保护个人自由、在享有公民自由、诉诸司法以及自由和自主的选举管理安排方面社会阶层平等的国家，不太容易受到不遵守的影响。欧洲人权法院的决定。对于案件层面的分析，侵犯权利的类型、判决中是否存在异议以及国家法官对其指定州的反对票都会影响州的合规行为。此外，研究的一个值得注意的结果是，如果国家法官对涉及任命他/她的国家的欧洲人权法院违规判决投反对票，则该判决很可能不会被被告国执行。