Binary classification is one of the popular classification problems in machine learning where we have to predict the class of a sample based on two categories like 1 or 0, true or false, yes or no, etc. If you want to learn how to solve binary classification problems with machine learning, this article is for you. In this article, I will take you through some of the best machine learning projects on binary classification.
Machine Learning Projects on Binary Classification
Spam Detection:
Spam detection is one of the most common binary classification problems in the data science community. Every newbie in data science tries this problem to figure out how to solve the binary classification problem. Here, you will be given a dataset of spam and not spam emails or messages, and your task here is to train a machine learning model to classify whether a message or email falls into the category of spam or ham (not spam). You can find this machine learning project on binary classification here.
Fake News Detection:
The detection of fake news is an advanced binary classification problem. It is also very popular among the data science community. Here, you will be given a dataset containing news headlines with labels as fake and real news, and your task here is to train a machine learning model to predict if the news is fake or real based on the news headlines. You can find many fake news detection datasets on the internet that use other data sources rather than the news headlines, but the way to solve this problem will remain the same. You can find this machine learning project on binary classification here.
Sarcasm Detection:
Sarcasm detection is another advanced problem of binary classification. Here your end goal is to predict whether a piece of text contains sarcasm or not. For this task, you will be given a dataset of texts containing sarcasm and texts without sarcasm, and your task will be to train a machine learning model that can predict whether a text contains sarcasm or not. You can find this machine learning project on binary classification from here.
If it is difficult for you to choose a machine learning algorithm based on the problem you are working on, here is a tip for you while working on the problem of binary classification. You can choose theĀ Bernoulli Naive BayesĀ algorithm to train a machine learning model for binary classification. It is the best algorithm for binary classification. If this does not give the best results, you can use the decision tree classification algorithm.
Summary
So these were some of the best machine learning projects based on binary classification that you can try. All these projects are solved and explained by using the Python programming language. Binary classification is one of the popular classification problems in machine learning where we have to predict the class of a sample based on two categories like 1 or 0, true or false, yes or no, etc. I hope you liked this article on machine learning projects on binary classification. Feel free to ask your valuable questions in the comments section below.
