#NaiveBayes скачать в хорошем качестве

#NaiveBayes

#NaiveBayes #Classifier #BayesAlgorithm Naive Bayes Classifier || Naive Bayes Algorithm Solved Example in very easy steps. In this video you will learn: 1. What is Naive Bayes algorithm? 2. How Naive Bayes Algorithms works? 3. Solved Example 4. What are the Pros and Cons of using Naive Bayes? 5. Applications of Naive Bayes Algorithm What is Naive Bayes algorithm? It is a classification technique based on Bayes’ Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. For example, a fruit may be considered to be an apple if it is red, round, and about 3 inches in diameter. Even if these features depend on each other or upon the existence of the other features, all of these properties independently contribute to the probability that this fruit is an apple and that is why it is known as ‘Naive’. The Naive Bayes model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods. Watch the complete video to know more. Do like, share, comment and subscribe my YouTube channel.