To reduce features in a dataset, two methods are there in machine learning: Feature selection and Feature extraction. Recursive feature elimination or in short RFE is the feature selection method. Here is given a complete guide on Recursive Feature Elimination for feature selection in machine learning. What is RFE? In Feature extraction, two or more features are combined from existing… Continue readingRecursive Feature Elimination(RFE): Effective Feature selection method in machine learning
Classification machine learning algorithms use probability to predict the correct class, such as Logistic regression, SVC, decision tree classifier, Lasso regression, etc. Naive Bayes is the supervised machine learning algorithm used for classification problems. Let’s see how it works. Principle of Naive Bayes classifier The Naive Bayes classifier is one of the fastest and simplest algorithms in machine learning. The… Continue readingNaive Bayes Classifier in machine learning- All you need to know
A machine learning pipeline consists of multiple data extraction, preprocessing, and model-building steps. It helps to automate processes that are required in model building. Pipeline helps to include all steps of preprocessing, feature selection, feature extraction, model selection, and model building In one entity. Here we will see how to make a pipeline in machine learning.