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Questions and Answers

What is the main objective of data integration in a data warehouse?

  • to combine multiple sources (correct)
  • to retrieve relevant data for analysis
  • to transform data into appropriate form for data mining
  • to identify the truly interesting patterns representing knowledge

    • What is the process of removing duplicate records called?

  • Data Mining
  • Data cleaning (correct)
  • Pattern evaluation
  • Knowledge presentation

    • What is the main goal of data mining?

  • to identify the truly interesting patterns representing knowledge
  • to transform data into appropriate form for data mining
  • to search for relationships and global patterns in large databases (correct)
  • to retrieve relevant data for analysis

    • What is KDD an abbreviation for?

    <p>Knowledge discovery in database</p> Signup and view all the answers

    What is the purpose of data selection in data mining?

    <p>to retrieve relevant data for analysis</p> Signup and view all the answers

    What is a data warehouse?

    <p>a single, complete and consistent store of data</p> Signup and view all the answers

    What is data transformation used for in data mining?

    <p>to transform data into appropriate form for data mining</p> Signup and view all the answers

    What is operational data used for?

    <p>used by particular departments or business groups</p> Signup and view all the answers

    What type of learning technique is used when a system explores data without any prior knowledge?

    <p>Unsupervised Learning</p> Signup and view all the answers

    Which clustering method is suitable for mixed numeric and nominal values?

    <p>K-Medoids</p> Signup and view all the answers

    What is the purpose of the linkage method in Agglomerative Clustering?

    <p>To merge or split clusters</p> Signup and view all the answers

    What is the output of the K-Medoids algorithm?

    <p>A set of medoids</p> Signup and view all the answers

    What is the primary difference between K-Means and K-Medoids?

    <p>The type of data handled</p> Signup and view all the answers

    What is the name of the clustering method that is robust to outliers?

    <p>K-Medoids</p> Signup and view all the answers

    What is the main advantage of Hierarchical Clustering?

    <p>Visualization of cluster structure</p> Signup and view all the answers

    Which library is used to import the AgglomerativeClustering class?

    <p>Scikit-learn</p> Signup and view all the answers

    What is the primary goal of data mining?

    <p>To extract models describing important data classes</p> Signup and view all the answers

    Which data mining method involves grouping data objects into a hierarchy or 'tree' of clusters?

    <p>Hierarchical Clustering</p> Signup and view all the answers

    What is the primary characteristic of unsupervised learning in data mining?

    <p>Finding natural grouping of instances given unlabeled data</p> Signup and view all the answers

    What is the primary advantage of using hierarchical clustering for data exploration?

    <p>It can be used for exploration</p> Signup and view all the answers

    What is the term for the process of extracting models describing important data classes?

    <p>Classification</p> Signup and view all the answers

    What is the primary difference between agglomerative and divisive hierarchical clustering algorithms?

    <p>Agglomerative is bottom-up, while divisive is top-down</p> Signup and view all the answers

    How many styles of hierarchical clustering algorithms are there to build a tree from the input set S?

    <p>2</p> Signup and view all the answers

    What is the term for the method that considers the distance between one cluster and another cluster to be equal to the shortest distance from any member of one cluster to any member of the other cluster?

    <p>Single linkage</p> Signup and view all the answers

    Study Notes

    Data and Information

    • Data refers to any facts, numbers, or text that can be processed by a computer.
    • Information is the awareness of data brought into relation to form knowledge in a wider sense.

    Types of Databases

    • Operational databases are owned by particular departments or business groups, such as sales or cost.
    • Informational databases are used for data analysis and reporting.

    Data Mining

    • Data mining is the search for relationships and global patterns that exist in large databases.
    • It involves transforming data into appropriate form for data mining through data cleaning, data integration, and data transformation.
    • Data selection is used to retrieve relevant data for analysis.

    Knowledge Discovery in Database (KDD)

    • KDD stands for Knowledge Discovery in Database.
    • It is the process of identifying valid, useful, and understandable patterns in data.

    Data Warehousing

    • A data warehouse is a single, complete, and consistent store of data obtained from a variety of different sources.
    • Data integration is the process of combining multiple sources of data into a single, unified view.

    Data Concepts

    • A fact is a simple statement of truth.
    • A principle is a general truth or law that is basic to other truths.
    • A procedure is a step-by-step action to achieve a goal.

    Data Mining Methods

    • Supervised learning is a method that builds models from data with predefined classes.
    • Unsupervised learning is a method that builds models from data without predefined classes.
    • Clustering is a form of data analysis that extracts models describing important data classes.

    Clustering

    • Hierarchical clustering is a method that works by grouping data objects into a hierarchy or “tree” of clusters.
    • Agglomerative clustering is a type of hierarchical clustering that starts with each object as its own cluster and merges them based on similarity.
    • Divisive clustering is a type of hierarchical clustering that starts with all objects in a single cluster and splits them based on similarity.

    K-Means and K-Medoids

    • K-means is a partitioning method that assigns each object to the cluster with the closest centroid.
    • K-medoids is a type of k-means clustering that uses medoids (objects that are representative of their cluster) instead of centroids (the mean of the cluster).

    Fuzzy Logic

    • Fuzzy logic is a many-valued logic system that allows for degrees of truth rather than simple true or false values.

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