Evidence Based Medicine pills
Evidence Based Medicine pills
Cramer's V allows the strength of the association between two categorical (nominal) variables, not ordinal, to be quantified. It is especially useful when the variables have multiple categories, since it allows the strength of the association to be condensed into a single figure. Its values range from 0, no association, to 1, a perfect association.
There are three important components involved in the training process of a machine learning algorithm: the loss function, the performance metric, and the validation control. The need to balance accuracy and predictive capacity to obtain robust and effective models is emphasized.
Contrary to what it could be supposed, the inclusion of a large number of variables in a linear regression model can be counterproductive to its performance, producing overfitting of the data and decreasing the capacity for generalization. This is known as the curse of multidimensionality.
Visual manipulation of data using poorly designed charts can distort data interpretation. The most common errors, such as missing axes, manipulated scales, and confusing pie charts, are described, which can lead to erroneous conclusions. Learning to detect these errors will allow us to improve our ability to visually analyze and interpret data.
Overfitting occurs when an algorithm over-learns the details of the training data, capturing not only the essence of the relationship between them, but also the random noise that will always be present. This negatively affects its performance and its ability to generalize when we introduce new data, not seen during training.