# Predicting Hard Disk Failure by Means of Automatized Labeling and Machine Learning Approach
## 5 Experimental Results
### Case Study
As for the levels of the number of leaves and the number of days of observation, the levels encode the values of 1000, 5000, 10,000 and 6, 7, 8, respectively. From the reported effects diagrams, it can be stated that for Ponza models, the proposed method gives better results using the RGF with \(L_{2}\) regularization on leaf-only models (\"\(RGF\)\") codified as the first level of the first factor. In a similar way, \(Expo\), 10,000 and 6 _days_ levels are chosen for the Loss Function, maximum number of leaves and observation interval for training, respectively. \begin{table}
\begin{tabular}{c l l} \hline
**SMART** & **Attribute Name** & **Description** \\ \hline
01 & Read Error Rate & \multicolumn{1}{c}{Hardware read errors that occurred when reading data} \\  & & from a disk surface \\
03 & Spin-Up Time & Average time of spindle spin up \\
04 & Start/Stop Count & Number of spindle start/stop cycles \\
05 & Reallocated Sectors Count & Quantity of remapped sectors \\
07 & Seek Error Rate & Frequency of errors while positioning \\
09 & Power-On Hours & Number of hours elapsed in the power-on state \\
10 & Spin Retry Count & Number of retry attempts to spin up \\
12 & Device Power Cycle Count & Number of power-on events \\
192 & Power-off Retract Count & Number of power-off or emergency retract cycles \\
193 & Load/Unload Cycle & Number of cycles into landing zone position \\
194 & HDA temperature & Temperature of a hard disk assembly \\
197 & Current Pending Sector Count & Number of unstable sectors (waiting for remapping) \\
198 & Offline Uncorrectable Sector Count & Number of uncorrected errors \\
199 & UltraDMA CRC Error Count & Number of CRC errors during UDMA mode \\ \hline \end{tabular}
\end{table} 
Table 2: Selected SMART Attributes [18]. \begin{table}
\begin{tabular}{c c c c c} \hline
**Experiment** & **Algorithm** & **Loss Function** & **Leaf** & **Days** \\ \hline
1 & RGF & LS & 1000 & 6 \\
2 & RGF & Expo & 5000 & 7 \\
3 & RGF & Log & 10,000 & 8 \\
4 & RGF\_Sib & LS & 5000 & 8 \\
5 & RGF\_Sib & Expo & 10,000 & 6 \\
6 & RGF\_Sib & Log & 1000 & 7 \\
7 & RGF\_Opt & LS & 10,000 & 7 \\
8 & RGF\_Opt & Expo & 1000 & 8 \\
9 & RGF\_Opt & Log & 5000 & 6 \\ \hline \end{tabular}
\end{table} 
Table 3: The design of the experiment. Similar behaviors have also been obtained for the other disk models; for the sake of brevity, they have not been reported. Choosing the levels associated with the maximum value in the effects diagrams for each parameter, the operating configuration capable of assuring the best prediction performance can be determined; the corresponding values are reported in Table 4 for the different disk models. Due to the discretization of the variation ranges, the DOE allows the developer to single out a sub-optimal operating configuration. This way, a manual tuning of the hyperparameters in a small neighborhood of the obtained configurations has been carried out in order to further improve the performance in the prediction stage; in particular, the performance index \(LR+\) has increased for some points. The first draft of performances are reported in Table 5. Using the sub-optimal configuration following the DOE, quite good performance values were obtained, but it is necessary to further reduce the False Positive Rate for the system in order to support maintenance. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & **Algorithm** & **Loss Function** & **Leaf** & **Days** \\ \hline Ischia & RGF\_Opt & Log & 10,000 & 7 \\ Capri & RGF & Log & 1000 & 8 \\ Ventotene & RGF\_Opt & Expo & 1000 & 8 \\ Procida & RGF\_Opt & LS & 10,000 & 7 \\ Ponza & RGF & Expo & 10,000 & 6 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimum Configuration. Figure 5: [PERSON]’s Effect Diagram. Therefore, it is necessary to increase the threshold beyond which a hard disk is considered close to failure. Finally, the optimal thresholds have been carried out by means of the ROC method (Figure 6). The associated final results are reported in Table 6; the remarkable results in FPR reduction can be appreciated.