# Explainability of Predictive Process Monitoring Results: Can You See My Data Issues?
## 5 Results
### Data- and Preprocessing-Related Observations
**Data relations after preprocessing**  
_Observation 4:_ _Mutual Information, i.e., the dependency between features and the label in event logs, has low values in most cases._  
An exception to this observation holds for the single-aggregated version of _BPIC2017_logs. As a remarkable observation, labels in these logs depend on the feature \"min_event_nr\",which remains among the top five highly dependent features with the label. In addition, these single-aggregated logs have a high dependency between aggregated forms of the \"timesinccesasetart\" feature, which is the most dependent feature on the label in the original form of these logs. The same observation holds in the single-aggregated version of _Sepsis2_, whereas \"remainingtime\" depends on the label with a coefficient of nearly 0.4, reflecting similar dependency in the original log with a lower coefficient. Studying correlations between features uncovers the following observations:  
**Observation 5.1**: _Two features are completely correlated across all event logs before and after applying the two preprocessing configurations, i.e., single aggregation and prefix index._  
To be more precise, these features are \"hour\" and \"timesincemidinight\". Note that these two features are artificial and their correlation is normal, as they are both extracted from  
Figure 5: Mututal Information analysis of _BPIC2017_Refused_ preprocessed with prefix index-configuration. the same original DateTime column. This observation draws our attention to the possible effect that adding artificial columns might have on the prediction process to be conducted. **Observation 5.2:** Certain domain-related features inherit correlations from the original logs and propagate this correlation in a strong form in the encoded versions of the same event log. **Example 3**. : _\"monthlycost\", \"numberofterms\", \"offeredamount\", and \"requestedamount\" are strongly correlated in the two versions of the BPIC2017 event logs. After applying single aggregation preprocessing the correlations remain the same, followed by correlations between aggregated versions of computed attributes such as \"timesincemidnight\", \"timesincelastevent\", and \"timesincceasstart\". The same happens after applying prefix index preprocessing, with longer prefixes suffering from multicollinearity between category levels of the same attribute, e.g., \"org:resource\"._  
**Example 4**. : _This example is present in the complete correlations (i.e., those equal to 1) between categorical levels of certain features, e.g., \"org:resource\" and \"dismissal\", along with many other high correlations. These high correlations appear in event logs with longer prefixes in Traffic_fines more frequently than in event logs with shorter prefixes._  
**Example 5**. : _Another example is manifested in the high collinearity between categorical attributes in original Sepsis logs, as shown in Figure 6 Such collinearity inherited as complete collinearity in those event logs obtained using either preprocessing configuration. However, the difference becomes obvious for numerical features in both preprocessing configurations. Partially, high correlations exist between aggregated forms of numerical features in single-aggregated event logs. Finally, only a few correlations exist between numerical features in shorter prefixes, increasing in number when prefixes become longer._  
**Observation 5.3:** High correlations emerge between features that are not correlated in the original log, while showing high correlations after applying both preprocessing configurations. **Example 6**. : _There are correlations in Traffic_fines event logs after preprocessing in which certain correlated features contain constant values._  
We can summarize the former observations by indicating the effect of a preprocessing configuration in magnifying the absence of a feature value when it is not available in certain events of a process instance, rather than the whole trace.