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AIA NC State Repositories
AIA NC State Repositories
3D-MICE (Multiple Imputation by Chained Equations): A statistical technique used to handle missing data by creating multiple imputed datasets. The "chained equations" approach iteratively fills in missing values by modeling each variable with missing data as a function of the others, cycling through the variables until the process stabilizes. This method is useful in datasets with complex interdependencies among variables.
Web Scraping: A technique used to automatically extract data from websites. Web scraping is used to gather large amounts of data from the web for analysis, typically using tools like BeautifulSoup, Scrapy, or Selenium in Python.
NLP Recommenders: Natural Language Processing (NLP) is used in building recommendation systems that understand and analyze human language to make personalized recommendations, such as suggesting books, movies, or articles based on user preferences.
Naïve Bayes: A simple yet powerful probabilistic classifier based on applying Bayes' theorem with strong (naïve) independence assumptions between the features. It's often used in text classification tasks such as spam detection or sentiment analysis.
Graph Search Scheduling: Refers to algorithms used to solve scheduling problems by representing them as graphs and using search algorithms like DFS (Depth-First Search) or BFS (Breadth-First Search) to find optimal schedules.
Logic Tests: Refers to a variety of logic-based assessments, potentially in the context of automated reasoning, constraint satisfaction problems, or logic programming. Examples include propositional logic or first-order logic tests.
C3+MAC+Backtracking: These are algorithms used in constraint satisfaction problems (CSPs). AC3 (Arc Consistency 3) is used for constraint propagation, MAC (Maintaining Arc Consistency) is an improvement over AC3 in backtracking search, and Backtracking is a basic search algorithm for CSPs.
Multi-arm Bandit Algorithms: A class of algorithms used in reinforcement learning to solve problems where an agent must choose between multiple strategies (arms) to maximize a cumulative reward. It's a classic example of the exploration-exploitation trade-off.
NetworkX Node Searches: NetworkX is a Python library for the creation, manipulation, and study of complex networks (graphs). Node searches in NetworkX could refer to various graph search algorithms like DFS, BFS, or shortest path algorithms applied to nodes within a graph.
Q-Learning Wumpus: Refers to applying Q-Learning, a reinforcement learning algorithm, to the Wumpus World, a common AI environment used to simulate decision-making in an uncertain and hazardous world. Q-Learning allows an agent to learn optimal actions based on rewards.
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