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

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expound

Przemys?aw Garsztka,Pawe? Kliberases in tomato crops using leaf images. The process involves building a convolutional neural network using a pre-trained VGG16 model that pre-processes the images according to its requirements and performs segmentation on images before training and testing the data. The model obtained an accuracy of

Misgiving

inflame

Katarzyna Kuziak,Krzysztof Pionteknd moth-flame optimization (MFO) are effective at optimising functions. This work introduces a novel hybrid sentiment-based SVM optimised by particle swarm and moth-flame algorithms (SVMPSOMFO) to improve predicting accuracy. SVMPSOMFO optimises the model’s parameter values by combining PSO and MFO,

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Krzysztof Piasecki,Joanna Siwekich 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

演繹

嚴(yán)厲批評(píng)

Irascible

Contemporary Trends in Local Governanceactory, 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

Dignant

deceive

Advances on Intelligent Computing and Data ScienceBig Data Analytics,