What are the advantages of Naive Bayes?
Answer: In Naïve Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data. The main advantage is that it can't learn interactions between features.
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Machine Learning
- Give a popular application of machine learning that you see on a day-to-day basis?
- What is Genetic Programming?
- In what areas is pattern recognition used?
- What is a classifier in machine learning?
- What is the difference between artificial learning and machine learning?
- What is algorithm independent machine learning?
- Explain what is the function of 'Supervised Learning'?
- What is the function of unsupervised learning?
- What is 'Training set' and 'Test set'?
- What is the standard approach to supervised learning?
- What are the three stages to build the hypotheses or model in machine learning?
- What are the different Algorithm techniques in Machine Learning?
- What are the five popular algorithms of Machine Learning?
- What is inductive Machine Learning?
- How can you avoid overfitting?
- Why does overfitting happen?
- What is 'Overfitting' in Machine learning?
- Mention the difference between Data Mining and Machine learning?
- What is Machine Learning?
- Give a derivation of for a single example in batch gradient descent? (Gradient Descent For Linear Regression)
- What is the algorithm for implementing gradient descent for linear regression?
- How does gradient descent converge with a fixed step size alpha?
- Why should we adjust the parameter alpha when using gradient descent?
- Why does gradient descent, regardless of the slope's sign, eventually converge to its minimum value?