This is post will share with you the Naive Bayes. What is Naive Bayes? Naive Bayes algorithm: a simple multi-class classification algorithm based on the Bayes theorem. It assumes that features are independent of each other. For a given sample feature X, the probability that a sample belongs ...
The Naïve Bayes classifier is a supervised machine learning algorithm that is used for classification tasks such as text classification.
Understanding Bayes’ theorem A strong foundation on Bayes theorem as well as Probability functions (density function and distribution function) is essential if you really wanna get an idea of intuitions behind the Naive Bayes algorithm. Bayes’ theorem is all about finding a probability (we call ...
1.5. Naive Bayes: Naive Bayes is a probabilistic machine learning algorithm commonly used for classification tasks, especially in natural language processing and text analysis. It’s based on Bayes’ theorem and makes predictions by calculating the probability of a data point belonging to a certain...
Naive Bayes: Naive Bayesis a classification algorithm that adopts the principle of class conditional independence from Bayes’ theorem. This means that the presence of one feature does not impact the presence of another in the probability of an outcome, and each predictor has an equal effect on...
【Udacity笔记】What is Machine Learning? 目录 Teaching computers to learn to perform tasks from past experiences(recorded data) 一、Decision Tree(决策树) ——Example:for recommend app 二、Naive Bayes Algorithm(朴素贝叶斯) ——Example:for detecting Spam e-mails(垃圾邮件)...
A support vector machine (SVM) is a type of supervised learning algorithm used in machine learning to solve classification and regression tasks. SVMs are particularly good at solving binary classification problems, which require classifying the elements of a data set into two groups....
These approaches differ fundamentally in how and when the model is built, affecting the algorithm’s flexibility, efficiency, and use cases. While both aim to classify data, they do so with contrasting methods that are suited to different types of tasks and environments. Let’s examine the ...
In reality, no one explicitly distinguishes between the conceptual model and the predictive model. Both are called the model. In short, the algorithm is the method of learning, and the model is what results form the learning phase. The model is the conceptual model (trees, svm, linear) trai...
Naive Bayes is a widely used classification algorithm that's used for tasks involving text classification and large volumes of data. Regression models Regression tasks are different, as they expect the model to produce a numerical relationship between the input and output data. Examples ofregression ...