Comparison of performance metrics, SVC vs QSVC after using NQE for data embedding. Bold-faced fonts denote that the classifier achieves better performance. by Aninda Astuti (21736334)

Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this an... by Aninda Astuti (21736334)

Flowchart for classification tasks in automated extinction risk assessment method, using the XGBoost algorithm [29]. by Gabriel Henrique de Oliveira Caetano (12647413)

Characteristics of the data sets used to evaluate Machine Learning and Deep Learning models for arboviral diseases classification. by Sebastião Rogério da Silva Neto (11944944)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”

Attributes found in the data sets. by Sebastião Rogério da Silva Neto (11944944)

Summary of all demographic, epidemiological and clinical data presented in data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

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)

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke by Chulho Kim (622686)

“…<div><p>Background and purpose</p><p>This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.…”

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Flowchart of the proposed Margin Weighted Robust Discriminant Score (MW-RDS) algorithm. by Sheema Gul (21519289)

Small-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Medium-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

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Comparison of ML and NLP algorithms for classifying the brain MRI reports. by Chulho Kim (622686)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... by Olaide N. Oyelade (14047002)

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some medium-sized dimensional data... by Olaide N. Oyelade (14047002)

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... by Olaide N. Oyelade (14047002)

Subjects: