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El Potaeto 2014-12-31 00:52:53 +01:00
parent 006578e2e6
commit c3d8f21df3
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R-package/demo/create_sparse_matrix.R
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@ -60,6 +60,6 @@ bst <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 3,
xgb.dump(bst, 'xgb.model.dump', with.stats = T)
# sparse_matrix@Dimnames[[2]] represents the column names of the sparse matrix.
importance = xgb.importance(sparse_matrix@Dimnames[[2]], 'xgb.model.dump')
importance <- xgb.importance(sparse_matrix@Dimnames[[2]], 'xgb.model.dump')
print(importance)
# According to the matrix below, the most important feature in this dataset to predict if the treatment will work is having received a Placebo or not.