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- Asymptotic Theorems (1)
- Bayesian Inferences (1)
- Central Limit Theorem (1)
- Correlated Random Variables (1)
- Cross Validation (1)
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- Manifold Data (1)
- NLP, Natural Language Processing, Cyberbullying, Twitter, classifcation, TF-IDF, bag-of-words (1)
- Noncentral F-distribution (1)
- Noncentral t-distribution (1)
- Observed significance level (1)
- P-value. (1)
- Posterior distributions and Regression Models. (1)
- Prior Sensitivity (1)
- Superconductor, critical temperature, regression, linear regression (1)
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Articles 1 - 5 of 5
Full-Text Articles in Statistics and Probability
Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown
Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown
The Journal of Purdue Undergraduate Research
No abstract provided.
Sensitivity Analysis Of Prior Distributions In Regression Model Estimation, Ayoade I Adewole, Oluwatoyin K. Bodunwa
Sensitivity Analysis Of Prior Distributions In Regression Model Estimation, Ayoade I Adewole, Oluwatoyin K. Bodunwa
Al-Bahir Journal for Engineering and Pure Sciences
Bayesian inferences depend solely on specification and accuracy of likelihoods and prior distributions of the observed data. The research delved into Bayesian estimation method of regression models to reduce the impact of some of the problems, posed by convectional method of estimating regression models, such as handling complex models, availability of small sample sizes and inclusion of background information in the estimation procedure. Posterior distributions are based on prior distributions and the data accuracy, which is the fundamental principles of Bayesian statistics to produce accurate final model estimates. Sensitivity analysis is an essential part of mathematical model validation in obtaining …
Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe
Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe
Data Science and Data Mining
Cyberbullying refers to the act of bullying using electronic means and the internet. In recent years, this act has been identifed to be a major problem among young people and even adults. It can negatively impact one’s emotions and lead to adverse outcomes like depression, anxiety, harassment, and suicide, among others. This has led to the need to employ machine learning techniques to automatically detect cyberbullying and prevent them on various social media platforms. In this study, we want to analyze the combination of some Natural Language Processing (NLP) algorithms (such as Bag-of-Words and TFIDF) with some popular machine learning …
Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe
Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe
Data Science and Data Mining
This project estimates a regression model to predict the superconducting critical temperature based on variables extracted from the superconductor’s chemical formula. The regression model along with the stepwise variable selection gives a reasonable and good predictive model with a lower prediction error (MSE). Variables extracted based on atomic radius, valence, atomic mass and thermal conductivity appeared to have the most contribution to the predictive model.
The Distribution Of The Significance Level, Paul O. Monnu
The Distribution Of The Significance Level, Paul O. Monnu
Electronic Theses and Dissertations
Reporting the p-value is customary when conducting a test of hypothesis or significance. The likelihood of getting a fictitious second sample and presuming the null hypothesis is correct is the p-value. The significance level is a statistic that interests us to investigate. Being a statistic, it has a distribution. For the F-test in a one-way ANOVA and the t-tests for population means, we define the significance level, its observed value, and the observed significance level. It is possible to derive the significance level distribution. The t-test and the F-test are not without controversy. Specifically, we demonstrate that as sample size …