What is Naive Bayes? Naive Bayes is an uncomplicated algorithm for machine learning that relies on Bayes’ theorem. It is frequently employed to accomplish classification tasks. Explain Bayes’ theorem in simple terms. Bayes’ Theorem determines the likelihood of an occurrence by considering previous information about the circumstances associated with the occurrence. Why is …
What is K-Means clustering? K-Means is an algorithm for clustering that divides a dataset into ‘k’ separate and non-overlapping subgroups, also known as clusters. How does K-Means work? K-Means operates by repeatedly designating data points to the closest cluster center and adjusting the cluster centers according to the average of the assigned points. …
What is Random Forest? Answer: Random Forest is an ensemble learning method that mixes numerous decision trees to generate a more robust and accurate model. How does a Random Forest work? Answer: During training, it creates numerous decision trees and outputs the average prediction (regression) or majority vote (classification) of the individual trees. …
What is K-Nearest Neighbors (KNN)? KNN is a straightforward, non-parametric, and supervised algorithm in machine learning that is employed for classification and regression purposes. It predicts outcomes by considering either the most prevalent class or the mean value of the k-nearest data points. How does KNN classify data points? KNN categorizes a data point …
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