## 3 Results
### CHAID Model  
A CHAID model was also constructed using a boosting technique, emphasising the accuracy of the model. The number of component models was ten, which were then utilised to train the boosted model. The estimated accuracy of the ensemble boosted model was 42.3% in the training set. This can be considered a better accuracy than a naive model with a 25% prediction accuracy. The coincidence matrix of the CHAID model is presented in Table 7.  
To evaluate the sensitivity, specificity, precision, and F-measure of the model, we recalculated the confusion matrix into a 4-field matrix for each category of the unemployment duration and then summed these individual tables to compute the macro- and micro-averages. The cumulative 4-field confusion matrix of model is presented in Table 8.  
The cumulative and individual tables were used to calculate the evaluation measures of this model, which we present in Table 9 for all categories (first four columns) of the target variable together with their macro- and micro-averages across the entire CHAID model (last two columns). All the mentioned measures were calculated for the testing set to depict the true quality of the model based on the data which were not used during the model's creation. The CHAID model demonstrated, similarly to the CART model, the best performance in identifying the category of jobseekers unemployed for more than 12 months, with a sensitivity of over 50%. The highest accuracy of 74.2% was \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Unemployment** & **Up to** & **3-6 Months** & **6-12 Months** & **More than** & **Sum** & **Correct [\%]** \\
**Duration** & **3 Months** & & **12 Months** & & **12 Months** & **Sum** & **Correct [\%]** \\ \hline
**up to 3 months** & 52,351 & 20,851 & 22,556 & 29,267 & 125,025 & 0.419 \\
3–6 months & 30,143 & 35,092 & 22,129 & 24,668 & 112,032 & 0.313 \\
6–12 months & 33,378 & 20,786 & 42,928 & 39,584 & 136,676 & 0.314 \\
**more than 12 months** & 30,784 & 16,771 & 26,399 & 76,626 & 150,580 & 0.509 \\
**sum** & 146,656 & 93,500 & 114,012 & 170,145 & 524,313 & 0.395 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Coincidence matrix of boosted CHAID model. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Unemployment** & **Sum Correct** & **Sum Incorrect** & **Sum** & **Correct [\%]** \\
**Duration** & **206,997** & 317,316 & 524,313 & **39.48** \\
**sum incorrect** & 317,316 & 1,255,623 & 1,572,939 & **79.83** \\
**sum** & 524,313 & 1,572,939 & 2,097,252 & **69.74** \\
**correct [\%]** & **39.48** & 20.17 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Cumulative confusion matrix for boosted CHAID model. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Evaluation** & **Up to** & **3–6 Months** & **6–12 Months** & **More than** & **Macro-Average** & **Micro-Average** \\
**Measure** & **3 Months** & & **12 Months** & & **12 Months** & **Macro-Average** \\ \hline
**sensitivity** & 41.87 & 31.32 & 31.41 & 50.89 & 38.87 & 39.48 \\
**specificity** & 76.38 & 85.83 & 81.66 & 74.98 & 79.71 & 79.83 \\
**precision** & 35.70 & 37.53 & 37.65 & 45.04 & 38.98 & 39.48 \\
**F-measure** & 38.54 & 34.15 & 34.25 & 47.78 & 38.68 & 56.60 \\
**accuracy** & 35.70 & 74.19 & 68.56 & 68.06 & 69.74 & 69.74 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Evaluation measures for boosted CHAID model. of jobseekers with unemployment lasting 3 to 6 months. That means that over 74% of jobseekers were correctly classified as either unemployed for this period or not. On the other hand, the model achieved a weaker performance in the category of jobseekers unemployed for up to 3 months but still functioned as a better model than a naive random prediction of unemployment duration. The accuracy of almost 70% can describe the overall performance of the CHAID model. This means that, on average, the model correctly predicted the duration of unemployment of jobseekers in almost 70% of cases. The sensitivity of the model is almost 39 (macro-average) to almost 40% (according to the micro-average).