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Jesus and the Cross - Biblical Archaeology Society Throughout the world, images of the cross adorn the walls and steeples of churches For some Christians, the cross is part of their daily attire worn around their necks Sometimes the cross even adorns the body of a Christian in permanent ink In Egypt, among other countries, for example, Christians wear a tattoo of the cross on their wrists And for some Christians, each year during the
How Was Jesus Crucified? - Biblical Archaeology Society Gospel accounts of Jesus’s execution do not specify how exactly Jesus was secured to the cross Yet in Christian tradition, Jesus had his palms and feet pierced with nails Even though Roman execution methods did include crucifixion with nails, some scholars believe this method only developed after Jesus’s lifetime
Why does scikits cross-validation return a negative R^2 for my . . . As I understand it, R^2 should be literally (0 7)^2 for a linear regression like this, and if there's some noise introduced by the cross-val split you'd expect it to be +- a decimal place or two, not a negative score
machine learning - Need advice regarding cross-validiation to obtain . . . Conclusion Cross-validation is a very important tool for selecting the regularisation parameter λ λ in LASSO regression By balancing model complexity and predictive performance, it helps to ensure that models generalise effectively to unseen data
The Staurogram - Biblical Archaeology Society The staurogram combines the Greek letters tau-rho to stand in for parts of the Greek words for “cross” (stauros) and “crucify” (stauroō) in Bodmer papyrus P75 Staurograms serve as the earliest images of Jesus on the cross, predating other Christian crucifixion imagery by 200 years Photo: Foundation Martin Bodmer
Cross-attention mask in Transformers - Data Science Stack Exchange Cross-attention mask: Similarly to the previous two, it should mask input that the model "shouldn't have access to" So for a translation scenario, it would typically have access to the entire input and the output generated so far So, it should be a combination of the causal and padding mask 👏 Well-written question, by the way
machine learning - How are parameters selected in cross-validation . . . Suppose I'm training a linear regression model using k -fold cross-validation I'm training K times each time with a different training and test data set So each time I train, I get different parameters (feature coefficients in the linear regression case) So I will have K parameters at the end of cross-validation How do I arrive at the final parameters for my model? If I'm using it to tune