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A comparative analysis of machine learning approaches for ...


A Comparative Analysis of Machine Learning Algorithms...

We used the following machine learning methods: logistic regression, random forest, and k-nearest neighbor (KNN). The logistic regression algorithm performed ...

Comparative Analysis of Machine Learning-Based Approaches for ...

The methodology presented in this paper combines both advanced machine learning algorithms and open-source based tools to correlate different data flows ...

A COMPARATIVE ANALYSIS OF MACHINE LEARNING AND DEEP ...

The research methodology involves a classification and comparative analysis approach. The goal is to compare the scalability and computational ...

Comparative analysis of various machine learning algorithms to ...

Bagging approach considers training multiple models independently on a training dataset, typically using the same learning algorithm. Each model ...

Comparative analysis of machine learning - ProQuest

The findings show that machine learning algorithms can estimate standard time, and the findings can be used for several purposes, including lowering production ...

A comparative analysis of machine learning methods for ...

Advanced analytical techniques are gaining popularity in addressing complex classification type decision problems in many fields including ...

A Comparative Analysis of Machine Learning and Deep Learning ...

Bioinformatics uses programming languages like Python, R, and Perl, statistical methods, and device gaining knowledge of techniques to investigate and interpret ...

A Comparative Analysis of Machine Learning Algorithms to Predict ...

Decision trees are less reliable and accurate than random forest. SVM solves nonlinear issues using kernel methods, whereas decision trees apply ...

A comparative analysis of machine learning and statistical methods ...

Qualitatively, statistical methods were reported to be more interpretable, less computationally expensive, less complex, and require less modeling knowledge. ML ...

Comparative analysis of machine learning algorithms for multi ...

The kernel applied in the SVM algorithm is critical for its way of functioning. Therefore, the learning and hyperparameters to be optimized also ...

Comparative analysis of Machine learning and Deep ... - IOPscience

Comparative analysis of Machine learning and Deep learning algorithms for Software Effort Estimation · Figures · Tables · References · Citations · Article data · Open ...

Comparative Analysis of Machine Learning Algorithms for Detecting ...

The algorithms were evaluated on metrics such as precision, recall, and F1-score, with the Passive Aggressive Classifier outperforming others, achieving a ...

A Comparative Study of Machine Learning Approaches on Learning ...

Dropout and failure rates in courses involving such topics are usually high, which has raised attention towards the development of strategies to attenuate this ...

Comparative Analysis of Machine Learning Approaches for Effective ...

Cardiovascular diseases are taken into consideration because the maximum existence-threatening syndromes with the huge mortality worldwide.

Comparative Analysis of Machine Learning Based Approaches for ...

This paper presents the different methods and models used by numerous researchers in literature to solve the issue of faces.

Comparative analysis of the rule-based and machine learning ...

Overall results revealed that the NLP algorithm embedded in the CourseMIRROR application is a good fit for assessing students' reflections and can be used to ...

Comparative analysis of machine learning methods for active flow ...

Title:Comparative analysis of machine learning methods for active flow control ... Abstract:Machine learning frameworks such as Genetic ...

A comparative analysis of machine learning - ProQuest

Based on the comparative analysis results, SVM (as the best-performed machine-learning technique) and fuzzy AHP methods were identified for the subsequent ...

Comparative analysis of machine learning methods for active flow ...

This work presents a comparative analysis of the two, benchmarking some of their most representative algorithms against global optimization techniques.

A Comparative Analysis of Machine Learning and Deep Learning ...

The results of our analysis showed that Artificial Neural Network (ANN) outperformed other machine learning algorithms with a maximum accuracy of 100%.