What is the difference between Gaussian, Multinomial and Bernoulli Naïve Bayes classifiers?
Gaussian Naive BayesGaussian Naive Bayes is useful when working with continuous values which probabilities can be modeled using a Gaussian
How to calculate Frequency table and Likelihood table for a Database in Naïve Bayes Algorithm?
We use Frequency and Likelihood tables for easy and simplification calculation of Prior and Posterior probability. The Frequency table contains the occurrence
What is the difference between Probability and Likelihood?
Probability is the percentage that a success occurs. For example, we do the binomial experiment by tossing a coin. We suppose that
How Naïve Bayes Theorem is termed or named as Naïve?
A naive Bayes classifier assumes that the presence or absence of a particular feature of a class is unrelated to the presence
How to derive Naïve Bayes Theorem?
Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of
What is the difference between Prior Probability and Posterior Probability?
Prior ProbabilityA prior probability is the probability that an observation will fall into a group before you collect the data.
What is the difference between Euclidean, Manhattan and Hamming Distances?
Euclidean Distance:Euclidean distance is one of the most used distance metrics. It is calculated using Minkowski Distance formula by setting p’s value to 2.
What are the Advantages and Disadvantages of KNN Classifier?
Advantages of KNN1. No Training Period: KNN is called Lazy Learner (Instance based learning). It does not learn anything in
Why cannot we use KNN for Large datasets?
KNN works well with a small number of input variables, but struggles when the number of inputs is very large. Each input
Why KNN Algorithm is called as Lazy Learner?
KNN algorithm is the Classification algorithm. It is also called as K Nearest Neighbor Classifier. K-NN is a lazy learner because