Explain Navie Bayes?
Posted On: Apr 01, 2020
Naive Bayes is a type of classification algorithm used to classify data based on the probabilistic classifiers. It is a collection of classification algorithms that uses Baye’s theorem. This theorem finds the probability of an event occurring given the probability of an already occurred other event.
//Baye’s Theorem mathematical equation P(A/B) = P(B/A) * P(A) / P(B)
Related Questions
Subscribe Our NewsLetter
Never Miss an Articles from us.
Recent Articles
Featured Categories
- Common Interview Questions
- Python Flask Interview Questions
- NoSQL Interview Questions
- jQuery Interview Questions
- C Programming Interview Questions
- AngularJs Interview Questions
- Node JS Interview Questions
- JavaScript Interview Questions
- Core Java Interview Questions
- HTML Interview Questions
- Laravel Interview Questions
- Wordpress Interview Questions
- PHP Interview Questions
Basic Machine Learning Interview Questions
What is machine learning?
Machine learning is the use of algorithms and data to perform specific tasks. ML is the process of giving the system the ability to learn from data using certain sophisticated algorithms. With the alg...
Basic Machine Learning Interview Questions
What supervised and unsupervised machine learning?
Supervised and unsupervised are the two types of Machine learning algorithms available. In the supervised type, the algorithms are applied to the known labeled data to formulate a model. Labeled data...
Basic Machine Learning Interview Questions
What is ROC curve?
ROC curve is a graphical plot to illustrate the ability of a classifier system. Basically, this curve tells you how much a binary classifier system is capable of distinguishing between classes. This c...