Contents
How does naive Bayes predict?
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.
What is true about naive Bayes?
Naive Bayes (NB) is ‘naive’ because it makes the assumption that features of a measurement are independent of each other. This is naive because it is (almost) never true. If this number is bigger then the corresponding calculation for class B then we say the measurement belongs in class A.
What are the advantages and disadvantages of Naive Bayes?
Naive Bayes is suitable for solving multi-class prediction problems. If its assumption of the independence of features holds true, it can perform better than other models and requires much less training data. Naive Bayes is better suited for categorical input variables than numerical variables.
Can Naive Bayes be used for multiclass classification?
Naive Bayes is a classification algorithm for binary (two-class) and multiclass classification problems.
What is the theory behind the naive Bayes classifier?
This article discusses the theory behind the Naive Bayes classifiers and their implementation. Naive Bayes classifiers are a collection of classification algorithms based on Bayes’ Theorem.
Are there any real world uses for naive Bayes?
In spite of their apparently over-simplified assumptions, naive Bayes classifiers have worked quite well in many real-world situations, famously document classification and spam filtering. They require a small amount of training data to estimate the necessary parameters.
What kind of distribution does a Gaussian naive Baye have?
In Gaussian Naive Bayes, continuous values associated with each feature are assumed to be distributed according to a Gaussian distribution. A Gaussian distribution is also called Normal distribution. When plotted, it gives a bell shaped curve which is symmetric about the mean of the feature values as shown below:
What is the formula for naive Bayes theorem?
Now, before moving to the formula for Naive Bayes, it is important to know about Bayes’ theorem. Bayes’ Theorem finds the probability of an event occurring given the probability of another event that has already occurred. Bayes’ theorem is stated mathematically as the following equation: