1. Please explain what is Perceptron in Machine Learning?

In Machine Learning, Perceptron is an algorithm for supervised classification of the input into one of several possible non-binary outputs.

2. Explain me what is Genetic Programming?

Genetic programming is one of the two techniques used in machine learning. The model is based on the testing and selecting the best choice among a set of results.

3. Tell me which method is frequently used to prevent overfitting?

When there is sufficient data ‘Isotonic Regression' is used to prevent an overfitting issue.

4. Explain what is ensemble learning?

To solve a particular computational program, multiple models such as classifiers or experts are strategically generated and combined. This process is known as ensemble learning.

5. Tell us what is dimension reduction in Machine Learning?

In Machine Learning and statistics, dimension reduction is the process of reducing the number of random variables under considerations and can be divided into feature selection and feature extraction

6. Tell me various approaches for machine learning?

The different approaches in Machine Learning are

☛ a) Concept Vs Classification Learning
☛ b) Symbolic Vs Statistical Learning
☛ c) Inductive Vs Analytical Learning

7. Tell us why ensemble learning is used?

Ensemble learning is used to improve the classification, prediction, function approximation etc of a model.

8. Do you know what is the standard approach to supervised learning?

The standard approach to supervised learning is to split the set of example into the training set and the test.

9. Tell me what are the advantages of Naive Bayes?

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.

10. Tell me when to use ensemble learning?

Ensemble learning is used when you build component classifiers that are more accurate and independent from each other.

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