What is multioutput regression? In a regression problem, the target variable is continuous in nature. A machine learning model predicts the continuous target variable based on the features. In a multioutput regression problem, there is more than one target variable....

We can use the make_classification() function to create a dataset that can be used for a classification problem. The function returns two ndarrays. One contains all the features, and the other contains the target variable. We can use the following Python code to...

We can use the make_regression() function in sklearn to create a dataset that can be used for regression. In other words, we can create a dataset using make_regression() and run a machine learning model on that dataset. The dataset will have a specific number of...

In one of our previous articles, we discussed what an Error Correcting Output Code (ECOC) classifier is and how it works. In this article, we will discuss how to implement an Error Correcting Output Code (ECOC) classifier with a Support Vector Machine Classifier (SVC)...

In our previous article, we discussed what an Error Correcting Output Code (ECOC) classifier is and how it works. In this article, we will discuss how to implement an Error Correcting Output Code (ECOC) classifier with logistic regression using sklearn in Python. We...