An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error

Statistical machine learning uses data to model a relationship between many parameters, or explanatory variables, and a response variable. The adaptive boosting algorithm is a machine learning method that can be used to model relationships of classification data. This method uses a weak base learner to improve accuracy of predicting the correct response class from a set of variables. Because of its learnability, adaptive boosting yields an exponentially decreasing empirical error. From this, an empirical error bound can be derived from the boosting algorithm. This empirical error bound inspires us to see if there is a generalized error bound and what form it takes. Evidence from boosting several real datasets will show that the generalized error follows the same shape as the empirical error, thus suggesting that a shift of the empirical error bound can create a generalized error bound. By simulating datasets from random and varying their characteristics based on criteria that seem to affect the shift, we can boost them and derive a function by which to shift the empirical error bound. We will record the test error of the boosted simulated datasets and build a regression model with that as the response and the varying characteristics of the datasets as the explanatory variables. The final regression model gives us the predicted outcome of the difference between the generalized error and the empirical error, thus enabling us to derive the suggested generalized error bound

Smokejumper Magazine, April 2001

This issue of the National Smokejumper Association (NSA) Smokejumper Magazine contains the following articles: Ride of My Life/malfunction on Shasta Trinity (Paige Houston), Tiniest Marine/Smallest Smokejumper, Gene DeBruin/MIA, profiles Ben Conner and Joe Blackburn, Jack Mathews Career with CIA. Smokejumper Magazine continues Static Line, which was the original title of the NSA quarterly magazine.https://dc.ewu.edu/smokejumper_mag/1030/thumbnail.jp

Dual Users: Real Lessons from Reality Television

This study attempts to understand the differences in activity among an emergent television/Internet audience. The Internet has provided a new entertainment opportunity for producers of television programming. Those television viewers who have also reached out to their favorite television show websites have resulted in a new audience. Examining the programming genre of reality television, two constructs were developed and a written survey administered to a convenience sample of college freshmen. The construct dual users was created to examine the television audience that also visits television programming websites. Single users (those that only watch the television show) were compared to the self-reported levels of activity and involvement of dual users. Early findings suggest that the dual users are more involved during viewing of the television show and engaged in less secondary activity than the single users

Racial Disparities and Risk for COVID-19 Among Pregnant Patients: Results from the Michigan Statewide Collaborative

Objective: Previous studies have looked at COVID-19 outcomes in pregnancy and racial disparities among patients with COVID-19, but few have studied racial disparities among pregnant patients with COVID-19. Our goal in this study is to analyze the relationship between race and disparate COVID-19 risk in pregnancy. Study Design: A retrospective cohort analysis was performed on data collected as part of the COVID-19 in Pregnancy and The Newborn: State of Michigan Collaborative, a database of pregnant patients admitted to 14 institutions in Southern Michigan. Cases were defined as patients with a positive SARS-CoV-2 test result. Controls, those with suspicion of COVID-19 prior to universal screening or a negative PCR test, were matched to cases on the same unit within 30 days of each case. For this analysis, the two primary groups of interest were non-Hispanic Black (Black) vs. non-Hispanic White (White) patients. Potential covariates were age, body mass index (BMI), chronic hypertension, diabetes, asthma, substance use, and smoking; the dependent variable was COVID/non-COVID in a robust Poisson regression model. In addition, 18 symptoms and disease severity (mild/moderate/severe) were compared between the Black and White groups using the same statistical method. Results: Of 1,131 gravidas, 42.9%(n=485) were Black. These patients were at two-fold greater risk for COVID-19 compared with their White counterparts [35.9% vs. 18.3%, RR=1.96(1.6-2.4)]. After adjusting for obesity and diabetes, the risk of COVID-19 in Black patients remained higher compared to the risk among White patients (aRR=2.46 [1.87-3.24]). There were no differences in symptoms nor severity of disease presentation between the groups. Conclusion: In our population, Black patients are more likely to be diagnosed with COVID-19 infection during pregnancy. This finding is not explained by a range of covariates. Other factors, such as social determinants of health, may be important to understand this disparity and warrant further examination

COVID-19 is associated with early emergence of preeclampsia: results from a large regional collaborative

Objective: To examine the relationship between COVID-19 and preeclampsia (PreE) in a large, diverse population. Study Design: The COVID-19 in Pregnancy and The Newborn: State of Michigan Collaborative established a database of pregnant patients admitted to 14 institutions in Southern Michigan. Patients with COVID-19 (cases) were matched to 2 or 3 non-COVID patients (controls) on the same unit within 30 days of each case. Relative Risks (RR) were calculated using robust Poisson regression models with adjustment for covariates. Chi-squared test for trend was used to assess the increase in risk with the severity of disease. Results: 369 cases and 1,090 controls were delivered between March - October 2020. An increased risk of PreE (RR=1.8), driven almost entirely by an increase in preterm PreE (pretermPreE) (RR=2.85) was observed in COVID pregnancies (Table 1), with a dose-response relationship with symptomatology and severity (Table 2). The associations between COVID-19 disease and PreE or pretermPreE were independent of other risk factors, as demonstrated by the minimal changes in RR after adjustment for confounders (Table 1). However, African American (AA) COVID patients experienced pretermPreE 1.9 times more than COVID patients of other races (10.1 vs 5.3), an increase not observed in control patients. The strength of the association for COVID with PreE was comparable to the association of PreE with chronic hypertension and nulliparity (data not shown). Increasing symptoms and severity of COVID-19 were associated with an increased risk for PreE with placental lesions, even after adjustment for relevant covariates (Tables 1 & 2). Non-PreE COVID patients had an increased trend of placental lesions compared to non-COVID patients, reaching significance for intravillous thrombin. Conclusion: COVID-19 is significantly associated with early emergence of PreE, independent of known risk factors other than AA race. Our study shows that among patients predisposed to PreE, COVID-19 impacts PreE severity in that it leads to pretermPreE. Further studies on COVID-19 and PreE, with a focus on racial disparities, is warranted