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author | Christoph Helma <helma@in-silico.ch> | 2018-03-23 15:48:48 +0100 |
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committer | Christoph Helma <helma@in-silico.ch> | 2018-03-23 15:48:48 +0100 |
commit | 2aad87d7d0159748ff2a68a0f15326eccf9977af (patch) | |
tree | 3bdf015178920cc32fa096ec4964f8cd29520bb2 | |
parent | bff63dfc03d903d5788051128d2d59e1b585f89b (diff) |
duplicated paragraph removedrevision
-rw-r--r-- | loael.Rmd | 5 | ||||
-rw-r--r-- | loael.md | 5 | ||||
-rw-r--r-- | loael.pdf | bin | 661959 -> 661574 bytes | |||
-rw-r--r-- | loael.tex | 6 |
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@@ -684,11 +684,6 @@ is required. This can be done in the graphical interface (<https://lazar.in-silico.ch>) which provides intuitive means of inspecting the rationales and data used for read across predictions. -Finally there is a substantial number of compounds -(`r length(unique(t$SMILES))-length(training$LOAEL_predicted)`), -where no predictions can be made, because there are no similar compounds in the training data. These compounds clearly fall beyond the applicability domain of the training dataset - and in such cases it is preferable to avoid predictions instead of random guessing. - Summary ======= @@ -625,11 +625,6 @@ is required. This can be done in the graphical interface (<https://lazar.in-silico.ch>) which provides intuitive means of inspecting the rationales and data used for read across predictions. -Finally there is a substantial number of compounds -(37), -where no predictions can be made, because there are no similar compounds in the training data. These compounds clearly fall beyond the applicability domain of the training dataset - and in such cases it is preferable to avoid predictions instead of random guessing. - Summary ======= @@ -825,12 +825,6 @@ This can be done in the graphical interface (\url{https://lazar.in-silico.ch}) which provides intuitive means of inspecting the rationales and data used for read across predictions. -Finally there is a substantial number of compounds (37), where no -predictions can be made, because there are no similar compounds in the -training data. These compounds clearly fall beyond the applicability -domain of the training dataset and in such cases it is preferable to -avoid predictions instead of random guessing. - \section{Summary}\label{summary} In conclusion, we could demonstrate that \texttt{lazar} predictions |