A standardized score is a score that has been adjusted to account for the distribution of scores in the data set. This adjustment allows comparisons of scores from different data sets.
Definition of Interpretability Interpretability: Interpretability is a measure of how easily a model’s predictions can be explained to humans. Models that are easy to interpret are more likely to be trusted and used in decision-making processes. Why does Interpretability matter? Interpretability is an important factor in how effective data science and machine learning tools are….
Ad Hoc Analysis is an exploratory analysis technique used to uncover patterns or relationships in a dataset. Often times this work is performed “Ad Hoc” or “On The Fly”… meaning it it done in the moment.
Definition of Probability Probability: Probability is a measure of how likely an event is to occur. It is calculated by dividing the number of times the event occurs by the total number of possible outcomes. It can be expressed as a number between 0 and 1, or as a percentage between 0% and 100%.
Definition of False Negative False Negative: False negative is a result of a test where a condition that is true is incorrectly reported as being false. What are the impacts of False Negatives? False Negatives can have a significant impact and be costly to data science and machine learning projects. False Negatives refer to instances…