## 5 Conclusions  
A typical software or a software package enables one to search for the rules in a database. The proposed method extends the scope of analysis by modifying the dataset. If values of any feature of a predecessor or a consequent are continuous or discrete, it is proposed to make them binary, and search--for a certain rule--for the set of thresholds dividing features' values into 0 and 1 (see Figure 2). The aim is to find the combination of these thresholds making the analyzed rule the most informative. As the three basic  
Figure 11: The 7-Score values of the rules for A-E-K and Cr-E-J-L for different numbers of days as the threshold of the head (delay).  
ratios (sup, conf, and lift) describe every rule, based on them, the measure is created and named as 7-Score. It was also necessary, owing to the need for applying the selected metaheuristic algorithm, to find the setup of thresholds maximizing the 7-Score for the analyzed rule. The results are superior when compared with the previous study. Moreover, the most informative rules are for the threshold of a construction project delay set to 0. As there are also projects in the database that were not delayed, it was decided to shift the threshold of the consequent up and observe the confidence (and other parameters) of the rule (or the set of the rules). It is concluded that the read-out is the construction risk of a delay in completion greater than the threshold (given in days). This risk decreases together with an increasing number of days. The 7-Score (the level of informativeness of the rule) decreases too. It is proved that, together with the threshold rising, the opposite rule, i.e., based on inverted consequent, is complementary to the basic rule. The sum of their confidences is 1. It can be read that the likelihood of completing a construction project (that meets the conditions of the predecessor) with the delay not greater than the threshold rises as the threshold increases. This innovative method of assessing the construction risk can be applied by clients and contractors. The results depend on the quality and size of the database being analyzed. The quality of data also refers to types of features creating the predecessor. They will be different for a contractor and for a client. Moreover, the consequent can describe a cost overrun, not exclusively delay. The invented method of risk assessment will be developed. The presented method of risk assessment is more accurate when more past cases are collected in the database. A given entity (a client or a contractor) with a rather short business history cannot expect precise quantitative risk estimations with the invented method. It is recommended to apply it to assess the risk of a contract for similar types of works. Despite that the type of contracted works can serve as an independent variable, the results will then be based on the limited number of cases. This lowers the accuracy of the method. However, the invented measure of the informativeness of association rules, i.e., 7-Score, can be broadly applied if the market basket analysis is applied.  
Conceptualization, H.A. and J.R.; methodology, H.A. and J.R.; software, J.R.; validation, H.A., J.R. and A.F.; formal analysis, A.F.; resources, H.A.; data curation, H.A., J.R. and A.F.; writing--original draft preparation, H.A. and J.R.; writing--review and editing, A.F. and J.R.; visualization H.A. and A.F.; supervision, A.F. and J.R.; project administration, A.F.; funding acquisition, H.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The database is published in [2]. As there is no electronic version of the Ph.D. thesis, data are available on request.