Titlebook: Advances in Machine Learning/Deep Learning-based Technologies; Selected Papers in H George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain Book

BABY

Semi-supervised Feature Selection Method for Fuzzy Clustering of Emotional States from Social Stream978-3-658-27226-5

tattle

Exploiting Semi-supervised Learning in the Education Field: A Critical Survey978-3-476-04367-2

貪心

Fallibility

syring

A Formal and Statistical AI Tool for Complex Human Activity Recognition978-3-658-07036-6

嗎啡

aggrieve

A Representative Energy Efficiency Project,in which the computer evaluates the performance of the human user with respect to the completion of an experiment, contributing further to an effective learning process. Hence, in order for the performance assessment to be accurate, two separate machine learning techniques, a genetic algorithm and b

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https://doi.org/10.1007/978-1-4471-4516-5r for building highly accurate and robust learning models. Over the last few years, a plethora of Semi Supervised Learning algorithms have been developed and implemented with great success for solving a variety of problems in many scientific fields, among which the education field as well. Following

nocturia

https://doi.org/10.1007/978-1-4471-4516-5data that cover a 1-year period were used. A python repository of automated time series forecasting models (AtsPy) was exploited to run the experiments. For the final comparison three different metrics (RMSE, MAE and MAPE) were taken into consideration. The results of this extended experimental proc