Supervised Learning

How to use lightGBM Classifier and Regressor in Python

How to use lightGBM Classifier and Regressor in Python LightGBM is a powerful machine learning library in Python that is used for both classification and regression tasks. It is designed to be fast and efficient, and it can be easily integrated into a variety of projects. In this blog post, we will be going over …

How to use XGBoost Classifier and Regressor in Python

How to use XGBoost Classifier and Regressor in Python XGBoost (eXtreme Gradient Boosting) is a powerful ensemble machine learning algorithm that creates multiple decision trees and combines their predictions to make more accurate predictions. It is widely used in Kaggle competitions and industry projects. It is used for both classification and regression problems. In this …

How to use GradientBoosting Classifier and Regressor in Python

How to use GradientBoosting Classifier and Regressor in Python Gradient Boosting is a powerful ensemble machine learning algorithm that creates multiple decision trees and combines their predictions to make more accurate predictions. It is used for both classification and regression problems. In this article, we will go over the basics of how to use Gradient …

How to use RandomForest Classifier and Regressor in Python

How to use RandomForest Classifier and Regressor in Python Random Forest is an ensemble machine learning algorithm that creates multiple decision trees and combines their predictions to make more accurate predictions. It is used for both classification and regression problems. In this article, we will go over the basics of how to use Random Forest …

How to create and optimise a baseline DecisionTree Model for Multiclass Classification in Python

How to create and optimise a baseline DecisionTree Model for Multiclass Classification in Python Decision Trees are a popular method of statistical analysis that can be used to predict a categorical variable based on a set of input variables. They are very helpful for both classification and regression problems. In this article, we will go …

How to create and optimise a baseline DecisionTree Model for Binary Classification in Python

How to create and optimise a baseline DecisionTree Model for Binary Classification in Python Decision Trees are a popular method of statistical analysis that can be used to predict a categorical variable based on a set of input variables. They are very helpful for both classification and regression problems. In this article, we will go …

How to check model’s accuracy using Cross Validation in Python

How to check model’s accuracy using Cross Validation in Python When building a machine learning model, it’s important to evaluate its accuracy to make sure it’s performing well. One technique for doing this is called cross-validation. Cross-validation is a method that allows to test the model’s accuracy by dividing the data into several parts, training …

IRIS Flower Classification using Logistic Regression Classifier

IRIS Flower Classification using Logistic Regression Classifier   IRIS flower classification is a common problem in machine learning. The IRIS dataset is a well-known dataset that contains information about different types of IRIS flowers, including their sepal length, sepal width, petal length, and petal width. The goal of IRIS flower classification is to use this …