Hierarchical clustering - Study guides, Class notes & Summaries

MATH 425 exam 2 all answers correct Unsupervised learning methods are needed when... data only contains features and no label What are some of the possible goals within unsupervised learning framework? One possible goal within the unsupervised learning framework is to discover interesting things about the data that you are working with. This includes questions such as "Are there any subgroups among the observations or variables that we can discover?", and "Do you notice any hi...

WPC 300 Final Exam (practice questions and answers) A-Graded 2024/2025 analytics - CORRECT ANSWER-the process of developing actionable decisions or recommendations for actions based upon insights generated from historical data primary data - CORRECT ANSWER-data collected specifically for the research problem at hand (ex: survey, interviews) secondary data - CORRECT ANSWER-data collected for some purpose other than the problem at hand (ex: firm's proprietary data, internet data, stock...

QMB3302 Final UF Verified A+ The correct number of clusters in Hierarchical clustering can be determined precisely using approaches such as silhouette scores (True or False) ️️False In K Means clustering, the analyst does not need to determine the number of clusters (K), these are always derived analytically using the kmeans algorithm. (True or False) ️️False One big difference between the unsupervised approaches in this module, and the supervised approaches in prior modules:...

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WGU C175/D426 DATA MANAGEMENT FOUNDATIONS OA EXAM ACTUAL EXAM 2 LATEST VERSIONS 300 QUESTIONS AND CORRECT ANSWERS ASSURED A+. VERSION A What does modality refer to? How does it appear on ER diagram? - ANSWERRefers to the MINIMUM number of times an instance in one entity can be associated with instance of another entity (minima) Appears as a 0 or 1 on the relationship line, next to cardinality Define: Referential Integrity - ANSWER- Requires that ALL foreign key values must either be fully ...

5 steps to building a machine learning model - 1. choosing a class of model 2. choose hyperparameters 3. arrange data 4. fit the model 5. predict a silhouette score of 1 is the [best/worst] and -1 is the [best/worst] score - best, worst basic idea of regression - we have some X values called features and some Y value, the variable we are trying to predict Difference between unsupervised and supervised learning - unsupervised: you have an X but no Y supervised: you have an X and a Y Ima...

AP Human Geography Unit 1 Multiple Choice Verified A+ A ratio of the number of items within a defined unit of area measures A. dispersion B. direction C. pattern D. density E. diffusion ️️D. density How is "sense of place" defined in human geography? Sense of place refers to the emotional connection people have with a specific location, often influenced by personal experiences, memories, and cultural significance. ️️ What is distance decay, and how does it inf...

Table of Contents Part 1: Introduction. The big picture of artificial intelligence and machine learning — past, present, and future. Part 2.1: Supervised Learning. Learning with an answer key. Introducing linear regression, loss functions, overfitting, and gradient descent. Part 2.2: Supervised Learning II. Two methods of classification: logistic regression and support vector machines (SVMs). Part 2.3: Supervised Learning III. Non-parametric learners: k-nearest neighbors, decision tree...

What does modality refer to? How does it appear on ER diagram? - ANSWERRefers to the MINIMUM number of times an instance in one entity can be associated with instance of another entity (minima) Appears as a 0 or 1 on the relationship line, next to cardinality Define: Referential Integrity - ANSWER- Requires that ALL foreign key values must either be fully NULL or match some primary key value 4 Ways Referential Integrity can be violated: - ANSWER- 1. Primary key is updated 2. Foreign key i...

What is Big Data? - Answer-Big data is a term which is used to describe any data set that is so large and complex that it is difficult to process using traditional applications. T/F: Big Data is an objective term? - Answer-False. Describe at least three sources of Big Data. - Answer-Archives, Machine logs, Public Web, Sensor Data, Social Media State and explain the characteristics of Big Data: Volume - Answer-The vast amount of data that must be dealt with. State and explain the character...