Most Asked Machine Learning Interview Questions and Answers

Machine Learning Interview Questions and Answers most commonly asked for Experienced PDF, Freshers candidates for Employment.

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.

What is Inductive Logic Programming in Machine Learning?

Inductive Logic Programming (ILP) is a subfield of machine learning which uses logical programming representing background knowledge and examples.

What is Model Selection in Machine Learning?

The process of selecting models among different mathematical models, which are used to describe the same data set is known as Model Selection. Model selection is applied to the fields of statistics, machine learning and data mining.

What are the two methods used for the calibration in Supervised Learning?

The two methods used for predicting good probabilities in Supervised Learning are

a)      Platt Calibration

b)      Isotonic Regression

These methods are designed for binary classification, and it is not trivial.

Which method is frequently used to prevent overfitting?

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

What is the difference between heuristic for rule learning and heuristics for decision trees?

The difference is that the heuristics for decision trees evaluate the average quality of a number of disjointed sets while rule learners only evaluate the quality of the set of instances that is covered with the candidate rule.

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.

Explain the two components of Bayesian logic program?

Bayesian logic program consists of two components.  The first component is a logical one ; it consists of a set of Bayesian Clauses, which captures the qualitative structure of the domain.  The second component is a quantitative one, it encodes the quantitative information about the domain.

What are Bayesian Networks (BN) ?

Bayesian Network is used to represent the graphical model for probability relationship among a set of variables .

Why instance based learning algorithm sometimes referred as Lazy learning algorithm?

Instance based learning algorithm is also referred as Lazy learning algorithm as they delay the induction or generalization process until classification is performed.

What are the two classification methods that SVM ( Support Vector Machine) can handle?

a)      Combining binary classifiers

b)      Modifying binary to incorporate multiclass learning

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.

Why ensemble learning is used?

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

When to use ensemble learning?

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

What are the two paradigms of ensemble methods?

The two paradigms of ensemble methods are

a)      Sequential ensemble methods

b)      Parallel ensemble methods


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