The algorithm which does not make strong assumptions are a non-parametric algorithm and they are free to learn from training data. The algorithm that makes strong assumptions are parametric and it involves select the form for the function and learn the coefficients
False Positive – A cancer screening test comes back positive, but you don’t have cancer False Negative – A cancer screening test comes back negative, but you have cancer True Positive – A Cancer Screening test comes back positive, and you have cancer True Negative – A Cancer Screening test comes back negative, and you don’t have cancer
Sensitivity means “proportion of actual positives that are correctly classified” in other words “True Positive” Specificity means “proportion of actual negatives that are correctly classified” “True Negative”