Questions
IS 4487-006 Fall 2025 Final Exam December 10 from 10:30 to 12:30
Matching
Match the following models with their general descriptions. 1: k-NN (k-Nearest Neighbors) 2: GMM (Gaussian Mixture Model) 3: Random Forest 4: Logistic Regression 5: Linear Regression 6: k-Means
Options
A.A non-parametric model that classifies data points based on the majority class of their nearest neighbors.
B.A text analytics model based on vectors of keywords.
C.A linear model that predicts the probability of a binary outcome using a logistic function.
D.A linear model that predicts a continuous target variable based on one or more input features.
E.The decision process that Chong Oh uses to select his breakfast foods.
F.An unsupervised clustering algorithm that partitions data into k clusters by minimizing intra-cluster variance.
G.Clustering method that finds overlapping, flexible-shaped groups
H.An ensemble learning method that combines multiple decision trees to improve classification or regression accuracy.
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Step-by-Step Analysis
Question restatement and options:
- The task presents 6 items to match with their general descriptions:
1) k-NN (k-Nearest Neighbors)
2) GMM (Gaussian Mixture Model)
3) Random Forest
4) Logistic Regression
5) Linear Regression
6) k-Means
- The available answer options are:
A) A non-parametric model that classifies data points based on the majority class of their nearest neighbors.
B) A text analytics model based on vectors of keywords.
C) A linear model that predicts the probability of a binary outcome using a logistic function.
D) A linear model that predicts a continuous target variable based on one or more input features.
E) The decision process that Chong Oh uses to select his breakfast foods.
F) An unsupervised clustering algorithm that partitions data into k clusters by minimizing intra-cluster variance.
G) Clustering method that finds overlapping, flexib......Login to view full explanationLog in for full answers
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