ML Project

Training set

Validation/developmet set: Which you use to tune parameters, select features, and make other decisions regarding the learning algorithm. Sometimes also called the hold-out cross validation set .

test set: which you use to evaluate the performance of the algorithm, but not to make any decisions regarding what learning algorithm or parameters to use.

of a cat classifier is the fraction of images in the dev (or test) set it labeled as cats that really are cats

is the percentage of all cat images in the dev (or test) set that it correctly labeled as a cat.

2/((1/Precision)+(1/Recall))

Also known as Jaccard Index, is a

measure to describe the extent of over- lap of predicted segmentation

mask with ground truth. It is defined as the intersection area between

the predicted segmentation and the ground truth, divided by the area of

union between the predicted segmentation mask and the ground truth:

IoU = J(A, B) = |A ∩ B|/(A ∪ B) = TP/(TP + FP + FN)

where A and B denote the ground truth and the predicted segmentation,

respectively, it goes between 0 and 1.