Idea on how classficiation in ML works!

Original article was published on Artificial Intelligence on Medium


Idea on how classficiation in ML works!

Let’s learn via example 🙂

As an example we’ll consider classifying an review.

Given a new review — determine whether the review is positive or negative!!

Important 1 : Classification is all about finding a function.

                   classification
new review (input)-----------------positive/negative review (output)

Yes classification is thought of finding a function.

How!! [ read below 🙂 ]

Important 2 : y = f(x)

x = input review text.

f = finding function ‘f’ is the classification.

y = outcome i,e review is positive review or negative review.

Overall → Important 2 says: Given an x, find the function f that will return y.

Let’s connect the dots.

Most of the Machine learning is thought of finding a function.

Let’s simplify “f” below.

                         algorithm
— — —
Training — — — — — — — -| f | → training phase
Dataset input — — —
learns

Core idea of classification:

                      — — — 
x — — — — — — — -| f | — — — — — — y → test/evaluation phase
input — — — output

x = input review text.
y = outcome i,e review is positive review or negative review.

This post was all about show casing the idea behind classification.

Thanks & Happy Learning 🙂