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Titlebook: Applications of Machine Learning; Prashant Johri,Jitendra Kumar Verma,Sudip Paul Book 2020 Springer Nature Singapore Pte Ltd. 2020 Fuzyy L

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楼主: Lincoln
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Neighborhood-Based Collaborative Recommendations: An Introduction,elms Internet users. Recommender systems (RSs) help individuals who are not able to make decisions from the potentially overwhelming number of alternatives available on the Web. Among various recommendation approaches, collaborative filtering-based recommender systems (CFRS) are the most popular (du
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Echo State Network Based Nonlinear Channel Equalization in Wireless Communication System,ted neurons. Only the reservoir-to-output readout mappings are variable and are modified during the process of training. ESN functions as a densely interconnected recurrent neural network and is suitable for temporal prediction tasks, but with significantly reduced training complexity. In this artic
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Melody Extraction from Music: A Comprehensive Study, research problem in MIR domain. Nowadays, the music providers have to facilitate searching of music based on their contents or recommend music based on users interest having identical contents. Melody extraction is mandatory to fulfill these user-interest driven searching and recommendation. The pr
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,Data Mining—A Tool for Handling Huge Voluminous Data,store of data which is growing speedily has motivated an emergent need for the development of automated tools in order to efficiently organize, examine and discover hidden information from the collected data. It is the initial stage where data is to be collected from heterogeneous sources and all ar
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Ensemble of Multi-headed Machine Learning Architectures for Time-Series Forecasting of Healthcare Ehitectures for multivariate time-series predictions has been less explored in the literature concerning healthcare domain. Multi-headed neural network architectures work on the idea that each independent variable (input series) can be handled by a separate neural network model (head) and the output
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Soft Computing Approaches to Investigate Software Fault Proneness in Agile Software Development Enve proposed model makes use of soft computing methods, like Mandani and Takagi–Sugeno style fuzzy inference system, artificial neural network, and adaptive neuro fuzzy inference system, for building fault prediction models. For achieving the goal of the study, several experiments are performed on the
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Week Ahead Time Series Prediction of Sea Surface Temperature Using Nonlinear Autoregressive Networkhey are the primary and early indicators of global imbalances that maliciously creep in the nature. Sea surface temperature is the foremost parameter that is observed to have a direct or indirect relationship to such variations. Literature surveys have revealed linkages of the sea surface temperatur
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