Given a parabola with focal length (f), we can derive the equation of the parabola. We assume the origin (h,k) = (0,0) of the coordinate system the parabola’s vertex(for easy calculations). For any point (x2,y2) on the parabola, the straight line from the focus(d1) and to the directix(d2) have theContinue Reading
Loss functions in ML(Machine Learning) are computational functions. These functions evaluate the price paid for inaccuracy of predictions in classification problems. Therefore, thier output should be minimized. The Loss Function used in Logistic Regression is cross entropy function: L(yˆ,y) = -(y*log(yˆ) + (1-y)*log(1-yˆ)) Where y is the ground truth outcomeContinue Reading
Logistic Regression can help predict specific values or categories with probability scores underlying the model’s classifications.Continue Reading
Similarity Measure The Jaccard index/coefficient, aka Intersection over Union is used in computer vision as one of the similarity measures for object detection on images. Formula The Jaccard similarity coefficient,aka Intersection over Union (IOU) score: Binary classification Formula The same score above can be described as binary classification as well to get anContinue Reading
Yair Shinar for Clarity and Solutions