Answer / Atul Kumar Singh

Naive Bayes is called Naive because it assumes that the presence or absence of a particular feature in a class is independent of the presence or absence of any other feature. This assumption may not always hold true, but even with this simplification, Naive Bayes can still perform well for many classification problems due to its computational efficiency and ability to handle large amounts of data.

Is r better than python for machine learning?

1 Answers  

---

Do you have research experience in machine learning?

0 Answers  

---

How do you think google is training data for self-driving cars?

1 Answers  

---

What is the benefit of naïve bayes mcq?

1 Answers  

---

What is bias-variance trade-off in machine learning?

1 Answers  

---

Is it better to have too many false positives or too many false negatives? Explain.

1 Answers  

---

What is collaborative filtering in machine learning?

1 Answers  

---

How to choose notable variables while working on a data set?

1 Answers  

---

Tell me what are your favorite use cases of machine learning models?

1 Answers  

---

Explain what is the function of ‘Unsupervised Learning’?

1 Answers  

---

How machine learning is deployed in real world scenarios?

1 Answers  

---

Tell us what's the difference between type I and type ii error?

1 Answers  

---