FAQ on Machine Learning

A Random Variable is a set of possible values from a random experiment. Example: Tossing a coin: we could get Heads or Tails. Rolling of a dice: we get 6 values   In the context of machine learning interview questions, the correct answer to “What is a random variable?” would be: A random variable is … Read more

A chi-square determines if a sample data matches a population. A chi-square test for independence compares two variables in a contingency table to see if they are related. A very small chi-square test statistics implies observed data fits the expected data extremely well.   In the context of machine learning, a chi-square test is a … Read more

The normal distribution is a bell-shaped curve. Most of the data points are around the median. Hence approximately 68 per cent of the data is around the median. Since there is no skewness and its bell-shaped.   The 68-95-99.7 (empirical) rule, also known as the three-sigma rule or the 68% rule, is a statistical guideline … Read more

The distribution having the below properties is called normal distribution. The mean, mode and median are all equal. The curve is symmetric at the center (i.e. around the mean, μ). Exactly half of the values are to the left of center and exactly half the values are to the right. The total area under the … Read more

Pruning helps in the following: Reduces overfitting Shortens the size of the tree Reduces complexity of the model Increases bias Pruning in the context of machine learning refers to the technique of reducing the size of a decision tree by removing certain branches and nodes. There are several benefits of pruning, including: Improved Generalization: Pruning … Read more