Category solved model papers

ID3 (Iterative Dichotomiser 3) is a supervised learning algorithm that constructs a decision tree using a greedy approach. It selects the best attribute at each level of the tree using…

A Decision Tree is a supervised learning model used for both classification and regression tasks. It classifies data instances with high accuracy and interpretability. The model follows an inductive inference…

Instance-based learning is called lazy learning because: Examples: Comparison: Instance-based vs. Model-based Learning Aspect Instance-Based Learning (Lazy) Model-Based Learning (Eager) Model creation No explicit model is created Learns a model…

Types of Regression Methods Limitations of Regression Methods

The Nearest Centroid Classifier is a simple alternative to k-Nearest Neighbors (k-NN) for similarity-based classification. It is also known as the Mean Difference Classifier. The key idea of this classifier…

The Weighted k-NN algorithm is an extension of the standard k-NN algorithm. Instead of treating all k neighbors equally, it assigns weights to neighbors based on their distance from the…

The k-NN algorithm relies on the assumption that similar objects exist close to each other in the feature space. It performs instance-based learning, meaning it stores the training instances and…

A machine learning model is an abstraction derived from training data that can make predictions on new, unseen data. The modeling process involves training a machine learning algorithm on a…

Version Space: A Version Space is the subset of hypotheses from the hypothesis space H that are consistent with all training instances. It includes only those hypotheses that correctly classify…

The Find-S algorithm is used to find the most specific hypothesis that is consistent with all positive instances in the training dataset. It: Given Training Dataset: CGPA Interactiveness Practical Knowledge…