# 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.

### How does it work?

When the algorithm has a probability for a hypothesis, it updates its hypothesis’s unreliable probability as it learns new evidence supporting or opposing the hypothesis, this will impact and ultimately determine the probability of the hypothesis’s accuracy.

The Naive Bayes algorithm is a classification model for binary, and multiclass classification problems.

The ‘Naive’ part of Naive Bayes is due to the calculation of the probabilities for each hypothesis. Each hypothesis is simplified to make its calculation tractable. It is assumed that each attribute or feature is conditionally independent, meaning that their value has no impact or relation to any other concerning features. The problem with this is that this is highly unlikely when working with real-world data and real-world problems.

Naive Bayes is generally used for a linear dataset, although this isn't always the case, it is the convention.

When deciding to use Naive Bayes, it isn't used in complex datasets, however, it is a good choice as an initial baseline for your problems. If Naive Bayes doesn't produce accurate results based on the chosen metric, it may be a good idea to entertain a new more sophisticated machine learning model, perhaps one that can separate non-linear data.

## Machine Learning Basics: Naive Bayes Classification

Understand the Naive Bayes Algorithm and solve a famous IRIS Dataset problem by implementing the Naive Bayes Classification Model. In this article, we shall go through the algorithm of the famous Naive Bayes Classification model with an example.

## Most popular Data Science and Machine Learning courses — July 2020

Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant

## Artificial Intelligence vs Machine Learning vs Data Science

Artificial Intelligence, Machine Learning, and Data Science are amongst a few terms that have become extremely popular amongst professionals in almost all the fields.

## AI(Artificial Intelligence): The Business Benefits of Machine Learning

Enroll now at CETPA, the best Institute in India for Artificial Intelligence Online Training Course and Certification for students & working professionals & avail 50% instant discount.

## Data science vs. Machine Learning vs. Artificial Intelligence

In this tutorial on "Data Science vs Machine Learning vs Artificial Intelligence," we are going to cover the whole relationship between them and how they are different from each other.