Description Usage Arguments Value Author(s) References See Also Examples
This function can be used for predicting the species labels for the fungal barcode sequences of the query set, using the model trained with reference barcode sequences.
1 | predict_test_funbarRF (object1, object2, m_try = 10, n_tree = 500)
|
object1 |
An object created by the function |
object2 |
An object created by the function |
m_try |
This parameter is required for |
n_tree |
This is also a parameter for |
A dataframe consisting of predicted species label for each sequence of the query dataset.
Prabina Kumar Meher, Division of Statistical Genetics,Indian Agricultural Statistics Research Institute, New Delhi-110012, INDIA
Liaw A., and Wiener M. (2002). Classification and Regression by randomForest. R News, 2(3), 18-22.
Meher P.K., Sahu T.K., and Rao A.R. (2016). Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier. Gene, 592(2), 316-324.
randomForest
, predict_train_funbarRF
, predict
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data (data_barcode)
train1 <- seq_funbarRF_manual (manual_seq=data_barcode$Fish$train[1:30])
test1 <- seq_funbarRF_manual (manual_seq=data_barcode$Fish$test[1:3])
res1 <- predict_test_funbarRF (object1=train1, object2=test1, m_try = 10, n_tree = 5)
# kindly use large number of n_tree
print(res1)
##################################
data (data_barcode)
train2 <- seq_funbarRF_manual (manual_seq=data_barcode$Inga$train[1:30])
test2 <- seq_funbarRF_manual (manual_seq=data_barcode$Inga$test[1:3])
res2 <- predict_test_funbarRF (object1=train2, object2=test2, m_try = 10, n_tree = 20)
# kindly use large number of n_tree
print(res2)
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