Logistic Regression is an extension of Linear regression, except that, here, the dependent variable is categorical and not continuous. It predicts the probability of the outcome variable.
So, Logistic Regression in one of the machine learning algorithm to solve a binary classification problem.
Some real-life classification examples would be :
Haar cascade classifier is an open cv algorithm. It makes classification between images with an object ( i.e face) and images without an object (i.e with non-faces).
Initially, several hundreds of images with face and several hundreds of images with non-faces have been given to this classifier. This classifier was then trained by applying machine learning methods like the neural networks to recognize human faces. It then extracted Haar Features from those images and stored them in an xml file.
Basically for face detection, the classifier looks for the most relevant features on the face such as eyes, nose, lips…
Electrical Engineer turned Data Analyst. The best way to learn any concept is by writing about it.