Titlebook: Big Data – BigData 2020; 9th International Co Surya Nepal,Wenqi Cao,Liang-Jie Zhang Conference proceedings 2020 Springer Nature Switzerland

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cacophony

A Performance Prediction Model for Spark Applicationsmber of configuration parameters that are strongly related to performance. Spark performance, for a given application, can significantly vary because of input data type and size, design & implementation of algorithm, computational resources and parameter configuration. So, involvement of all these v

拉開這車床

Predicting the DJIA with News Headlines and Historic Data Using Hybrid Genetic Algorithm/Support Vectors. We first examine two state-of-the-art AI techniques, hybrid genetic algorithm/support vector regression and bidirectional encoder representations from transformers (BERT). After that, we proposed a new AI model that uses hybrid genetic algorithm/support vector regression and BERT to predict da

針葉樹

休戰(zhàn)

Dorsal-Kyphosis

使高興

A Web Application for Feral Cat Recognition Through Deep Learningnd detect the number of . feral cats of Australia using deep learning algorithms targeted to data captured from a set of remote sensing cameras. Feral cat recognition is an especially challenging application of deep learning since the cats are often similar and, in some cases, differ only in very sm

arthrodesis

愛管閑事

CANDY

Ensemble Learning for Heterogeneous Missing Data Imputationl and model-based methods. While the former brings bias to the analyses, the latter is usually designed for limited and specific use cases. To overcome the limitations of the two methods, we present a stacked ensemble framework based on the integration of the adaptive random forest algorithm, the Ja