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.

What is symbolic planning?

1 Answers  

---

Explain the Algorithm Technique of Learning to Learn in Machine Learning?

1 Answers  

---

Explain why Navie Bayes is so Naive?

1 Answers  

---

Is coding required for machine learning?

1 Answers  

---

What kind of problems lend themselves to machine learning?

1 Answers  

---

Explain me how would you handle an imbalanced dataset?

1 Answers  

---

Tell me what are the last machine learning papers you've read?

0 Answers  

---

What is the difference between bayesian and frequentist?

1 Answers  

---

Explain the machine learning techniques?

1 Answers  

---

How do I become an expert in machine learning?

1 Answers  

---

Why ensemble learning is used?

1 Answers  

---

What is the difference between artificial intelligence and machine learning?

1 Answers  

---