The ideas for expansion have flown the coop, jumped the tracks and completely lost the plot of why the College Football Playoff was created. Big Ten boss Tony Petitti's model is the latest example.

Statistical analyses included correlation studies, diversity indices, and multinomial logistic regression adjusted for potential confounders such as stress, contraceptive use, age, and body mass ...

Mathematical Models Recently, mathematical models using logistic-regression and Bayesian networks have been developed in order to predict the outcome of PULs ( Table 1 ).

Serum progesterone and HCG levels, mathematical models and other factors can help predict the outcomes of pregnancies of unknown location (PULs). What is involved in the management of women with PULs?

Bee-swarm plots of feature importance within the Ordered Multinomial Logistic Regression model for practice prediction. The x -axis represents the individual variables and the y-axis indicates their ...

The statistical analysis is based on a multinomial logistic regression model, allowing the identification of factors associated with FCS and HDDS. We found that the HDDS is high (61%) for households ...

The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific disciplines.

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...

Binary logistic regression is a classification method that generalizes logistic regression to multiclassification problems, namely, problems with more than two possible discrete outcomes. In the ...

On the basis of a multinomial logistic regression analysis, the following factors were confirmed as being significantly associated with ADT combination therapy with ARPI (Table 2): more recent index ...