Description Usage Arguments Details Examples
View source: R/predict_targetted.R
This function generates training and prediction datasets for whole proteome to predict 1/n_fold of the proteome by the other n-1 fold data.
1 2 3 | generate_training_test_data_t(lower_bound = -1, upper_bound = 1,
positive_training_feature_file, negative_training_feature_file,
negative_predict_feature_file, output_label_training, output_label_predict)
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lower_bound |
The lower bound of the scaled data range, default to -1. |
upper_bound |
The upper bound of the scaled data range, default to 1. |
positive_training_feature_file |
A Rds file containing the positive training features(generated by g_feature_t()). |
negative_training_feature_file |
A Rds file containing the negative training features(generated by g_feature_t()). |
negative_predict_feature_file |
A Rds file containing the negative prediction features(generated by g_feature_t()). |
output_label_training |
The string to tag the output files associated with training proteins. |
output_label_predict |
The string to tag the output files associated with prediction proteins. |
This function outputs formatted feature files ready for Liblinear training and prediction.
1 2 3 4 5 6 | generate_training_test_data_t(lower_bound = -1, upper_bound = 1,
positive_training_feature_file ="ps_training_noc_not_na_pos_feature.Rds",
negative_training_feature_file = "ps_training_noc_not_na_candi_feature.Rds",
negative_predict_feature_file = "ps_predict_noc_not_na_candi_feature.Rds",
output_label_training = "ps_training",
output_label_predict = "ps_predict")
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