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Titlebook: Business Intelligence; 7th International Co Mohamed Fakir,Mohamed Baslam,Rachid El Ayachi Conference proceedings 2022 Springer Nature Switz

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Mining Frequents Itemset and Association Rules in Diabetic Datasetction of association rules by FP-Growth algorithm and its variants using a diabetic dataset, which are the CFP-Growth and ICFP-Growth. Experimental results show that the ICFP-Growth is more accurate than CFP-Growth and FP-Growth.
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1865-1348 , Morocco, during May 26-28, 2022. ..The 23 full papers included in this book were carefully reviewed and selected from a total of 68 submissions. They were organized in topical sections as follows: decision support and artificial intelligence; business intelligence and database; and optimization an
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Alberto Del Bimbo,Pietro Pala,Enrico Vicariot diseases based on convolutional neural networks using one of the most widely used datasets. The model should be a solution that enables farmers to identify the early blight and late blight diseases present in their potato plants thus they can choose the appropriate treatment.
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A Convolutional Neural Networks-Based Approach for Potato Disease Classificationt diseases based on convolutional neural networks using one of the most widely used datasets. The model should be a solution that enables farmers to identify the early blight and late blight diseases present in their potato plants thus they can choose the appropriate treatment.
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Optimization Focused on Parallel Fuzzy Deep Belief Neural Network for Opinion Mininge data quality and remove noisy data. Then, we have applied a semi-automatic data labeling over the dataset by combining two techniques: Vader lexicon and Mamdani’s fuzzy system. In addition, we have used four extraction techniques, which are: TFIDF (Unigram), TFIDF (Bigram), TFIDF (Trigram) and Glo
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