How to apply LightGBM Classifier to adult income dataset LightGBM is a gradient boosting framework that uses tree-based learning algorithms. It is designed to be efficient and scalable, allowing it to work well on large datasets. In this essay, we will be discussing how to apply the LightGBM Classifier to predict adult income using …
Month: April 2020
How to apply CatBoost Classifier to adult income dataset CatBoost Classifier is a powerful ensemble machine learning algorithm that is specifically designed to handle categorical features, which are features that take on a limited number of discrete values. It is an open-source library developed by Yandex, and it is built on top of …
How to apply XGBoost Classifier to adult income dataset XGBoost Classifier is a powerful ensemble machine learning algorithm that is similar to Gradient Boosting Classifier but with additional features and optimization techniques that make it more efficient and effective. In this essay, we will be discussing how to apply the XGBoost Classifier to predict …
How to apply Gradient Boosting Classifier to adult income data Gradient Boosting Classifier is an ensemble machine learning algorithm that builds multiple weak models and combines their predictions to improve the overall performance of the model. In this essay, we will be discussing how to apply the Gradient Boosting Classifier to predict adult …
How to compare Bagging ensembles in Python using adult income dataset Ensemble methods are a set of machine learning techniques that combine multiple models to improve the performance of the final model. Bagging ensembles are a popular type of ensemble method that combines the predictions of multiple base models to reduce the variance and …
How to apply sklearn Extra Tree Classifier to adult income dataset Extra Trees Classifier is an ensemble machine learning algorithm that is similar to Random Forest Classifier but with a slight difference in the way the decision trees are built. In this essay, we will be discussing how to apply the Extra Trees Classifier …
How to apply sklearn Random Forest Classifier to adult income dataset Random Forest Classifier is an ensemble machine learning algorithm that builds multiple decision trees and combines their predictions to improve the overall performance of the model. In this essay, we will be discussing how to apply the Random Forest Classifier to predict …
How to apply sklearn Bagging Classifier to adult income data Bagging Classifier is an ensemble machine learning algorithm that combines the predictions of multiple base models to improve the overall performance of the model. In this essay, we will be discussing how to apply the Bagging Classifier to predict adult income using the …
How to apply sklearn decision tree algorithm to adult income data Decision Tree is a popular supervised machine learning algorithm that can be used for both classification and regression tasks. It creates a tree-like model of decisions and their possible consequences, which can be used to predict the outcome of a new observation. …
Binary Classification using GaussianNB, MultinomialNB, BernoulliNB classifiers Binary classification is a type of supervised learning where the goal is to predict one of two possible outcomes, such as “positive” or “negative”. The Naive Bayes Classifier is a popular algorithm for binary classification, and it is implemented in the scikit-learn library (sklearn) in three …