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In terms of random forests, the number of variables randomly sampled as candidates at each . Note that the default values are different for classification
In terms of random forests, the number of variables randomly sampled as candidates at each . Note that the default values are different for classification (sqrt(p) where p is number of variables in x) and regression (pf3) O a. split 0 b. tree 0 c. prediction 0 d. forest 0 e. leaf Which variable would be considered to be the most important based on the variable importance summary below? # 2 3 MeanDecreaseAccuracy MeanDecreaseGini # palmitic 6. 201296e-03 0. 0014379784 3. 308227e-03 1. 5004802 # palmitoleic 1.251152e-02 0. 0080258716 9. 780941e-03 5. 3855391 # stearic 1.832261e-02 0. 0032159991 9. 083142e-03 2.9723542 oleic 2. 743528e-01 0. 1068586362 1. 716261e-01 42. 1517807 # linoleic 3. 145757e-01 0. 1706523172 2. 261581e-01 44 . 6474290 # linolenic 5.628296e-02 0. 0176726008 3. 265775e-02 7. 3087267 # arachidic 5.973604e-02 0. 0161886015 3. 318951e-02 14. 2631284 # eicosenoic -9.286749e-05 0. 0001100443 1. 525958e-05 0. 080332 O a. arachidic O b. palmitic O c. stearic O d. linoleic O e. oleicFrom a single tree, as in the one below, what variable would be considered the most important? yes ] eicoseno >= 7 no 1 linoleic >= 1054 3 O a. eicosenoic O b. none of these O c. linoleic O d. oleic O e. arachidicWhat does this paragraph refer to? In every tree grown in the forest, put down the oob cases and count the number of votes cast for the correct class. Now randomly permute the values of variable m in the oob cases and put these cases down the tree. Subtract the number of votes for the correct class in the variable-m- permuted oob data from the number of votes for the correct class in the untouched oob data. The average of this number over all trees in the forest is the raw importance score for variable m. O a. OOB error O b. prediction of new cases O c. variable importance O d. vote matrix O e. proximityWhat input in the randomForest function, from the randomForest package, controls the number of variables selected at each tree split? O a. it doesn't have an input parameter for this O b. proximity O c. confusion O d. mtry O e. ntree
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