ব্যাখ্যা
In machine learning, inductive reasoning is commonly used. It involves generalizing from specific instances or examples to form broader generalizations or patterns. This reasoning process is crucial in machine learning because algorithms learn from data and make predictions or inferences based on observed patterns in the training data.
Inductive Reasoning in Machine Learning:
•Inductive reasoning allows a system to draw conclusions about unseen data based on previously observed examples.
•In machine learning, inductive learning refers to the process of learning patterns or models from data and then generalizing these patterns to new, unseen instances.
•For example, a machine learning algorithm may learn to recognize images of cats by being trained on a dataset of labeled cat images and then generalize this understanding to recognize new, unlabeled images of cats.
Source: Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig