Answer / Anubha Rastogi

Naive Bayes is a classification algorithm based on applying Bayes' Theorem with strong independence assumptions between the features. It assumes that the presence of a particular feature does not affect the presence or absence of any other feature. This assumption allows for efficient implementation, but can lead to suboptimal results in certain cases.

Explain the benefit of naive bayes in machine learning?

1 Answers  

---

What is dimensionality reduction? Explain in detail.

1 Answers  

---

What do you understand by the confusion matrix?

1 Answers  

---

Name the three types of algorithms?

1 Answers  

---

What is the classification threshold in machine learning?

1 Answers  

---

If a highly positively skewed variable has missing values and we replace them with mean, do we underestimate or overestimate the values?

1 Answers  

---

What is data standardization in ml?

1 Answers  

---

How will you know which machine learning algorithm to choose for your classification problem?

1 Answers  

---

What do you understand by selection bias?

1 Answers  

---

Explain Ensemble learning technique in Machine Learning?

1 Answers  

---

Give a popular application of machine learning that you see on day to day basis?

1 Answers  

---

What is kernel SVM?

1 Answers  

---