Multivariate Linear Regression is similar to linear regression but instead of having single dependent variable Y, we have multiple output variables. It may be written as, Y = XB + U
In the last post we learnt about Linear regression with one variable. What if, we have more than one independent variables or features. As we could see, with more independent variables, our model exactly fits the training data.
Python has several ML libraries but major libraries that are used are the following:
Numpy, Scikit-Learn, Pandas..
Classification: It is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.