## 3 Methods  
The task is to assess the feasibility of predicting whole rock geochemistry parameters with spectral data used as the driving input to the model/s. The combined HyLogger and FTIR spectral data comprise 1476 spectral bands. To reduce computational overhead and to reduce the dimensionality of the spectra we firstly use a non-negative matrix factorization (NMF) model [27] and follow that with a random forest regression (RFR) model [18] to make our prediction. The model implementations for the NMF and RFR are provided by the python scikit-learn library [28].  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Dataset** & **Statistic** & **Fe** & **SiO2** & **Al2O3** & **TiO2** & ** CaO** & **MgO** & **K2O** & **LOI** \\ \hline Train/Val & mean & 41.70 & 24.53 & 4.94 & 0.23 & 1.31 & 1.05 & 0.24 & 7.34 \\  & std & 18.67 & 21.91 & 5.98 & 0.39 & 5.17 & 3.46 & 0.73 & 7.44 \\  & 50\% & 43.85 & 16.16 & 2.49 & 0.08 & 0.04 & 0.09 & 0.01 & 5.68 \\  & 75\% & 58.74 & 44.53 & 6.48 & 0.27 & 0.09 & 0.25 & 0.05 & 8.74 \\  & max & 69.15 & 98.70 & 53.38 & 8.63 & 52.47 & 22.00 & 9.36 & 84.79 \\ Set 2 & mean & 41.18 & 25.83 & 5.32 & 0.27 & 0.98 & 0.80 & 0.17 & 7.21 \\  & std & 17.62 & 21.95 & 6.29 & 0.42 & 4.47 & 3.05 & 0.56 & 7.05 \\  & 50\% & 41.74 & 18.93 & 2.71 & 0.09 & 0.04 & 0.08 & 0.01 & 5.63 \\  & 75\% & 57.29 & 46.14 & 7.25 & 0.34 & 0.08 & 0.19 & 0.04 & 8.94 \\  & max & 69.29 & 96.51 & 55.92 & 10.10 & 39.70 & 21.50 & 12.10 & 73.82 \\ Set 3 & mean & 43.68 & 22.92 & 4.08 & 0.19 & 0.99 & 0.81 & 0.17 & 7.64 \\  & std & 17.66 & 22.33 & 4.92 & 0.33 & 4.25 & 2.75 & 0.56 & 6.33 \\  & 50\% & 47.90 & 11.87 & 2.30 & 0.08 & 0.04 & 0.09 & 0.01 & 6.34 \\  & 75\% & 59.18 & 42.94 & 5.14 & 0.20 & 0.09 & 0.22 & 0.04 & 9.21 \\  & max & 68.13 & 96.76 & 51.72 & 7.76 & 49.87 & 20.80 & 11.60 & 73.23 \\ Set 4 & mean & 45.66 & 23.01 & 4.78 & 0.20 & 0.11 & 0.14 & 0.12 & 5.83 \\  & std & 16.12 & 20.52 & 5.70 & 0.31 & 0.96 & 0.57 & 0.44 & 3.05 \\  & 50\% & 48.99 & 15.94 & 2.50 & 0.08 & 0.03 & 0.06 & 0.01 & 5.36 \\  & 75\% & 59.56 & 40.11 & 6.07 & 0.24 & 0.05 & 0.10 & 0.03 & 7.81 \\  & max & 68.77 & 97.65 & 39.19 & 6.84 & 48.73 & 18.50 & 7.65 & 42.96 \\ Set 5 & mean & 43.36 & 25.37 & 4.57 & 0.22 & 0.34 & 0.32 & 0.13 & 6.44 \\  & std & 15.68 & 21.05 & 5.42 & 0.33 & 2.68 & 1.76 & 0.41 & 4.61 \\  & 50\% & 44.33 & 19.45 & 2.36 & 0.08 & 0.01 & 0.05 & 0.01 & 5.64 \\  & 75\% & 57.46 & 44.26 & 6.29 & 0.29 & 0.03 & 0.11 & 0.03 & 8.43 \\  & max & 67.32 & 97.73 & 51.14 & 5.96 & 40.53 & 21.00 & 6.85 & 47.01 \\ Set 6 & mean & 43.00 & 23.52 & 5.67 & 0.31 & 0.48 & 0.59 & 0.24 & 6.85 \\  & std & 17.34 & 21.43 & 6.16 & 0.48 & 2.76 & 2.11 & 0.67 & 4.83 \\  & 50\% & 45.74 & 14.59 & 3.15 & 0.12 & 0.02 & 0.06 & 0.01 & 6.10 \\  & 75\% & 58.11 & 43.35 & 8.75 & 0.46 & 0.06 & 0.21 & 0.10 & 9.09 \\  & max & 69.49 & 96.89 & 51.29 & 25.20 & 42.55 & 20.70 & 6.49 & 46.89 \\ Set 7 & mean & 41.25 & 26.53 & 5.32 & 0.28 & 0.56 & 0.71 & 0.28 & 6.41 \\  & std & 17.46 & 21.85 & 6.14 & 0.45 & 2.96 & 2.29 & 0.74 & 5.33 \\  & 50\% & 41.30 & 20.73 & 2.70 & 0.10 & 0.03 & 0.10 & 0.01 & 5.40 \\  & 75\% & 56.80 & 46.11 & 7.82 & 0.36 & 0.09 & 0.34 & 0.08 & 8.80 \\  & max & 69.49 & 97.66 & 48.03 & 8.63 & 37.42 & 20.40 & 7.07 & 46.76 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The summary statistics comprised of the mean, standard deviation, 50% and 75% quartiles, and the maximum value of the 7 datasets and the 8 geochemical parameters examined in the study.