Explain Navie Bayes?
Posted On: May 13, 2024
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 harnesses algorithms and data to accomplish tasks, imbuing systems with the capacity to learn from data. Sophisticated algorithms facilitate the construction of mathematical models, e..
Basic Machine Learning Interview Questions
What supervised and unsupervised machine learning?
two types of Machine Learning: Supervised, using labeled data to predict outcomes, and Unsupervised, finding hidden structures in unlabeled data...
Basic Machine Learning Interview Questions
What is ROC curve?
ROC curve visualizes classifier's ability to distinguish classes via TPR and FPR, crucial for evaluating model performance...