Naive Bayes is a type of classifier that employs the Bayes Theorem. It calculates membership probabilities for each class, such as the likelihood that a given record or data point belongs to a specific class. The most likely class is the one with the greatest probability.
Naive Because it presupposes class conditional independence, Bayes classification is referred to as naive. The effect of an attribute value on a specific class is independent of the other attributes' values. This assumption is made to reduce computational costs and hence is considered Naive.
Predicting the class of the test data set is simple and quick. It also excels at multi-class prediction. When the assumption of independence is met, a Naive Bayes classifier outperforms alternative models such as logistic regression, and less training data is required.
Learner's Ratings
4.6
Overall Rating
56%
44%
0%
0%
0%
Reviews
P
Priya Singh
4
good
R
Rohit Khare
4
What will be the mandatory requirement of configuration of PC for this ML tool
M
Muhammad Fahad Bashir
5
Explained the concept easily
P
Pradeep Kumar Kaushik
5
Please give me iris,csv file.
A
Ankit Malik
4
where is the finaldata.csv
V
Vimal Bhatt
5
great learning plateform kushal sir is really too good
Share a personalized message with your friends.