Titlebook: Advances on Intelligent Computing and Data Science; Big Data Analytics, Faisal Saeed,Fathey Mohammed,Mohammed Al-Sarem Conference proceedi

VOC

腼腆

A Comparison Study of Machine Learning Algorithms for Credit Risk Predictionich are used to determine if transactions are good or bad. The findings of data analysis using Logistic Regression, Linear Discriminant Analysis, Gaussian Naive Bayes, K-Nearest Neighbors Classifier, Decision Tree Classifier, Support Vector Machines, and Random Forest are compared and contrasted in

鄙视读作

Forecasting Tourist Arrivals Using a Combination of Long Short-Term Memory and Fourier Seriesaccuracy. The efficiency of the proposed model is compared using monthly tourism arrivals data from Langkawi Island, which has a notable pattern and seasonality. The findings reveal that the proposed model is more reliable than the other models in forecasting tourist arrivals series.

DALLY

Age and Gender Classification from Retinal Fundus Using Deep Learning8.61%, whilst accuracy is 98.62%. There is a prevalent non-awareness among clinicians regarding the changes in retinal variable variances among age and gender, emphasizing on the necessity of model explain ability of the age and gender classification of the images of retinal fundus. DL may assist cl

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Heart Disease Prediction Using a Group of Machine and Deep Learning Algorithmsactory, as it was capable of predicting evidence of having a heart condition in a specific patient utilizing DL and the ML Model (Random-Forest-Classifier) that had high accuracies when compared to other employed classifiers. The proposed DL methodology for predicting heart disease is going to impro

心胸狭窄

缺陷

Małgorzata Iwanicz-Drozdowska,Paweł Smagaive reviews after the release of the movie include different types of content: some are about the movie itself, some are because of “辱华”, and some mention “腾讯”. This study can benefit large-scale decision-makers on matters related censorship and filtering.

Indict

Małgorzata Olszak,Iwona Kowalskaroaches from the literature were used to make comparisons. The results showed that the minimum voltage magnitude was increased by 8.4%, from 0.913 to 0.990 p.u. Furthermore, the total real power loss was reduced by 36.76%, indicating significant network performance and operational improvements. In a

HAWK

Katarzyna Kochaniak,Paweł Ulmanm Forest (RF), Support Vector Machine (SVM), Naive Bayes (NB),and K-nearest neighbor (KNN) are the five classification methods used in this study. The LightGBM model provides a more accurate forecast. Comprehensive testing is used to determine the overall effectiveness of the LightGBM at the level o

freight

Katarzyna Kochaniak,Paweł Ulman Language Processing (NLP) techniques and three main tasks are deployed: corpus analysis, term extraction, and concept conceptualisation. As for the ML-based stage, it is based on semi-supervised ML techniques and three main tasks are applied: taxonomic classification, semantic mapping, and knowledg