Decision algorithm for classification of samples based on the data obtained with the new multiplex qPCR. by Fernanda Saloum de Neves Manta (8871500)

Summary of all non-clinical data (laboratory and others) presented in the data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

Function of signature-based and anomaly-based IDS. by Nasrullah Khan (13778350)

Algorithms used in this study. by Daniel Sanchez-Gomez (19065975)

“…This allowed us to develop a machine learning-based framework for the prediction of bead-forming minerals by training and benchmarking 13 of the most widely used supervised algorithms. …”

Hi-C read-pair classifications. by Matthew Z. DeMaere (6404834)

DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf by Marcel Dahms (9160118)

Prediction model development of late-onset preeclampsia using machine learning-based methods by Jong Hyun Jhee (3367859)

“…The combined use of maternal factors and common antenatal laboratory data of the early second trimester through early third trimester could effectively predict late-onset preeclampsia using machine learning algorithms. …”

Performance of the case classification system. by Quirine ten Bosch (13250509)

Interpretation of the Asante Rapid Recency Assay results is based on the presence or absence of specific lines. by Ernest L. Yufenyuy (12494849)

Subjects:

Flow chart of the proposed methodology. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Confusion matrix of RF. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Literature review comprising main studies. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

NSL-KDD dataset results. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Confusion matrix of RF. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Confusuion matrix of AdaBoost. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

CIC-2017 dataset training period. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

The accuracy result on NSL-KDD dataset. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Confusuion matrix of CataBoost. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Accuracy results on the CIC-IDS2017 dataset. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”

Confusuion matrix of AdaBoost. by Nasrullah Khan (13778350)

“…The proposed process is based on the following steps: (1) training the data using RNNs, (2) extracting features from their hidden layers, and (3) applying various classification algorithms. …”