Titlebook: Machine Intelligence and Smart Systems; Proceedings of MISS Shikha Agrawal,Kamlesh Kumar Gupta,Manish Gupta Conference proceedings 2022 Th

议程

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音的强弱

苦恼

978-981-16-9652-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

NATTY

Progesterone

腐蚀

Deep Learning Implementation for Dark Matter Particle Detection,s data as generated by 2008 Hadron Collider experiment and developed neural network model using deep neural network wherein the network was developed using PyTorch with multiple level of hidden layers to understand the particle properties and is able to categorize the particles. Further, we name the

希望

Ensemble Semi-supervised Machine Learning Algorithm for Classifying Complaint Tweets,thms and features dataset of 1000 tweets to validate out approaches. The result of F1 score as 88% and accuracy as 89% clearly indicate that our approach is quite promising in identifying the compliant data.

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Processes

Comparative Analysis of Machine Learning Algorithms for Imbalance Data Set Using Principle Componen technique principle component analysis (PCA). The preprocessed data set is evaluated with various standard ML algorithms (decision tree, support vector machine, neural network analysis, etc.).The evaluation of the data set has been recording accuracy and precision values of unbalanced to balanced d