№ files_lp_4_process_3_123219
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University data mining course assignment describing dataset preparation, clustering experiments with K-means and DBSCAN, and evaluation of clustering quality using an R implementation of a purity metric.
Course: COSC 4335
Institution: University-level computer science course
Instructor: Dr. Eick
Document Type: Course assignment
Subject Area: Data Mining and Clustering Algorithms
Algorithms Covered: K-means, DBSCAN
Programming Language: R
Datasets: Complex8 dataset; HAbalone dataset (modified Abalone dataset)
Original Dataset Source: UCI Machine Learning Repository Abalone Dataset
Project Type: Individual project
Learning Objectives: Clustering analysis, interpretation of clustering results, R function development, unsupervised data mining analysis, use of background knowledge in data mining
Assignment Tasks: Dataset transformation; implementation of purity evaluation function; clustering analysis with K-means and DBSCAN
Submission Deadline: March 18, 2015, 11p (early submission bonus)
Final Deadline: March 24, 2015, 11p
Document Version: Fourth Draft
Last Updated: Feb. 16, 2015, 2:30p
Price: 8 / 10 USD
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Ensemble Techniques and Unsupervised Learning: Model Combination, Voting, Bagging, Boosting, Stacking, K-means, KNN, Gaussian Mixture Models, and Expectation Maximization
Year: 2022
Subject: Machine Learning, Ensemble Methods, Unsupervised Learning
Document Type: Educational Unit / Lecture Notes
Author: Not specified
Target Audience: Students and researchers in machine learning
Techniques Covered: Model combination, Voting schemes, Bagging, Boosting, Stacking, K-means clustering, K-nearest neighbors, Gaussian mixture models, Expectation maximization
Scope: Theoretical explanation of ensemble learning and unsupervised methods, including algorithm generation and combination strategies
k-Means Programming Exercises
Year: 2026
Region / City: Worldwide
Topic: Machine Learning, Clustering
Document Type: Programming Exercises
Author: Todd W. Neller
Target Audience: Students, Researchers, Data Scientists
Period of Validity: Ongoing
Approval Date: N/A
Date of Changes: N/A
ECED 4335 Language and Literacy in the Early Years Syllabus, Spring 2026
Institution: The University of Texas at El Paso
College: College of Education
Department: Department of Teacher Education
Course Title: Language and Literacy in the Early Years
Course Code: ECED 4335
CRN: 25077 and 28523
Credits: 3
Semester: Spring 2026
Instructor: Arleen Y. Mendez, M.A.
Instructor Email: [email protected]
Course Format: Fully Online
Schedule: Monday – Sunday
Required Textbook: Morrow, L. M. (2019). Literacy Development in the Early Years: Helping Children Read and Write (9th edition). Pearson.
Subject Area: Early Childhood Education; Language and Literacy Development
Academic Policies: Standards of Academic Integrity; Responsible Use of Generative AI
Support Services: UTEP Library; University Writing Center; UTEP Helpdesk; ATLAS Lab; Technology Support Center
Copyright Notice: Course site content copyrighted by UTEP and ECED faculty
Do Not Resuscitate (DNR/DNI) Orders in School Emergency Response Policy 4335
Document number: 4335
Topic: Emergency medical response in schools
Type of document: Board of Education policy
Organization: Board of Education
Subject: Handling of Do Not Resuscitate / Do Not Intubate orders for medically fragile students
Related procedures: Individual health care plan development and review
Participants mentioned: School nurse (licensed registered nurse), parent or guardian, school personnel, Section 504/IEP team
Emergency protocol: Contact emergency medical services (911) and provide emergency care within staff training
Medical documents referenced: Do Not Resuscitate (DNR) orders, Do Not Intubate (DNI) orders
Target population: Students, including medically fragile students
Institutional principle: Students must not be denied genuine and appropriate efforts to preserve life and health
Legal reference: GS
Adoption status: Adopted
Topics: DBSCAN K-means 4335