Which of the learning methodology applies conditional probability of all the variables with respective the dependent variable?

Which of the learning methodology applies conditional probability of all the variables with respective the dependent variable?

A. Reinforcement learning

B. Unsupervised learning

C. Artificial learning

D. Supervised learning

View Answer

Answer: D

Explanation:

Supervised learning is a type of machine learning where we train a model using labeled data. In this learning paradigm, the model learns from the training data to make predictions or infer mappings. Conditional probability often plays a role in this, especially in algorithms like Naive Bayes, where the goal is to compute the probability of a certain class given the features (variables) of the data, which is fundamentally a conditional probability.

Here’s a brief rundown of the other options:

A. Reinforcement learning: This is about agents who take actions in an environment to maximize cumulative reward. It’s not centered around conditional probability of variables.

B. Unsupervised learning: This is about finding patterns in data without labeled responses. Methods such as clustering and dimensionality reduction fall into this category.

C. Artificial learning: This is not a standard term in the field of machine learning or data science.