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Probabibites Reference

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6 documents available in our comprehensive collection of Probabibites Reference resources. Find practical guides, tutorials, and documentation to enhance your knowledge.

Preview of Endometrial Adenocarcinoma Prognosis and Survival Analysis
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Endometrial Adenocarcinoma Prognosis and Survival Analysis (sdrtodxfsokkiaconverter.pdf)

184 KBbarchryEN 2 pages
The text describes a software converter ("Sdrtodxfsokkiaconverter") and includes a reference to a medical study on endometrial adenocarcinoma survival rates and relapse probabilities based on different treatment approaches
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Preview of Machine Learning
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Machine Learning (L11.1-prob-models.pdf)

1002 KBEN 45 pages
Machine learning and data mining involve probabilistic modeling to handle uncertain inferences from data. Probability theory is used to model uncertainty, enabling inference and prediction through probabilities. Applications include machine learning, computer vision, and NLP.
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pdf (2020.findings-emnlp.70.pdf)

1.18 MBHengyi Cai ; Hongshen Chen ; Yonghao Song ; zhuoye Ding ; Yongjun Bao ; Weipeng Yan ; Xiaofang ZhaoEN 10 pages
Neural dialogue response generation has gained popularity, but models trained with Maximum Likelihood Estimation (MLE) objective function suffer from...
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Preview of etherpad text
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etherpad text (IVOA_DAL_RM13.pdf)

45 KBEtherpadEN 4 pages
The IVOA DAL WG Running Meeting #13 discussed the status of LineTAP, a TAP view based on VAMDC focused on common use cases.
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Preview of Forecasting IBOVESPA Index with Fuzzy Logic
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Forecasting IBOVESPA Index with Fuzzy Logic (Newton-e-Outros.pdf)

221 KBEN 17 pages
This research applies fuzzy logic to predict the direction of price changes for the São Paulo Stock Exchange Index (IBOVESPA), utilizing 2,000 daily data points from January onwards. It offers a novel method for stock market forecasting.
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Preview of arXiv:0907.4010v1 [stat.CO] 23 Jul 2009
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arXiv:0907.4010v1 [stat.CO] 23 Jul 2009 (0907.4010v1.pdf)

101 KBEN 10 pages
It addresses challenges in Bayesian inference for models with censored or order-restricted parameters, where analytical computations are difficult. The methods utilize accept-reject sampling, Gibbs sampling, and Markov Chain Monte-Carlo techniques.
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