In Stock Market, Data mining play very important role to analysis of data. Data techniques can be applied on past and present financial data to generate pattern and decision making. In this paper, we have used predictive techniques like Decision Tree DT, Random Forest RF, Support Vector Machine SVM, Random Tree RT and Multilayer Perceptron MLP for and …
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· Frédéric Magoulès is Professor at the Ecole Centrale Paris in France and Honorary Professor at the University of Pècs in Hungary. His research focuses on parallel computing, numerical linear algebra and learning. Hai-Xiang Zhao is Senior Researcher at Amadeus in France. His research focuses on parallel computing, data and learning.
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Data Data Learning Text Predictive Jobs - Check out latest Data Data Learning Text Predictive job vacancies @monstergulf.com with eligibility, salary, location etc. Apply quickly to various Data Data Learning Text Predictive job openings in top companies!
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and Prediction using K-Means Clustering & Decision Tree Algorithm By Ananya Sarker, S.M. Shamim, Dr. Md. Shahiduz Zama & Md. Mustafizur Rahman . Abstract- Employee is the key element of the organization. The success or failure of an organization depends on the employee .
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Cost Service continues to be a useful reference on a wide range of topics for early stage mine planning through to ‘fill the gaps’ on more detailed studies. Cost Service provides an independent source for information on equipment, quantities and cost for a significant number of methods and range of production rates.
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Engineer for Caterpillar Large Trucks. and system dynamic simulation, test evaluation and validation. productivity and efficiency .
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. The efficiency, effectiveness or success of an activity or an entire process is referred to as . can be measured using various key figures.Such key figures can affect the cycle time or costs of a process, for example. If key figures such as these have been included, they can be used to perform a .
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learning methods were applied to both the raw version and the feature engineered version of the data sets, to predict the students success. The thesis comes to the same conclusion as the earlier studies: The results show that it is possible to predict student successfully by using learning. The
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· This paper presents the study of data in the education industry to model the for students enrolled in university. Two algorithms of data were used. Firstly, a descriptive task based on the K-means algorithm was utilized to select several student clusters. Secondly, a classification task supported two classification ...
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This Study conducted in 993students from college of computing and informatics within Wolkite University with respective departments. We were using WEKA open source software to test the prediction of the student . It provides many different algorithms for data and learning. WEKA is open source and freely available.
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predictive model by analyzing the microseismic data. The proposed model utilizes two learning algorithms, Topological Data TDA for the feature extraction from the microseismic data and Support Vector …
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· Abstract. In this paper, the performance of an AntMiner mining machine containing 189 chips on three printed circuit board PCBs is experimentally studied. The numerical method is applied to analyze the local airflow and distribution alongside the flow direction and shows a good agreement with the experimental results.
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