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Flashcards

Data

Johan Isaksson Data mining Inglês 15 flashcards

Flashcards do conjunto (15)

  1. 1Scalar attributesNominal, Ordinal, Interval, Ratio
  2. 2NominalProvides only enough information to distinguish one object from another
    (==, =/=) ex) zip codes, employee ID, eye color
  3. 3OrdinalValues provide enough information to order objects (<,>) ex) grades, {good, better, best}, 1-5 etc
  4. 4IntervalThe differences between values are meaningful, i.e. unit of measurement exists (+, -) ex) calendar dates, Celsius etc
  5. 5RatioBoth differences and ratios are meaningful (/, *) ex) Kelvin, age, electrical current
  6. 6Discrete attributesHas only a finite or countable set of values, often represented as integer values
    ex) zip codes, counts, set of words in a document
  7. 7Continuous attributesReal numbers as attributes typically represented as floats
    ex) temperature, height, weight
  8. 8Data quality problemsNoise, outliers, duplicates, missing values
  9. 9AggregationCombining two or more objects (or attributes) into a single object (or attribute)
    Data reduction -> less variability = more stable
  10. 10SamplingEntire set of data is too expensive and/or time consuming to work with
    Representative sample = same properties as original set
    Larger sample size = more accurate but loses point of sampling
  11. 111. Simple random 2. Without replacement 3. With replacement 4. Stratified sampling1. Equal probability for all
    2. Selected item removed from population
    3. Selected item not removed from pop.
    4. Split data into partitions, then draw randomly from each partitions
  12. 12Curse of dimensionalityWhen dimensionality increases, data becomes more sparse, so density and distance, which is important for some methods, means less
  13. 13Feature subset selectionRemove redundant and irrelevant features
    Done through: brute force, embedded, filter, wrapper
  14. 14Feature creationCreate new attributes that capture important information more efficiently than original data set
  15. 15Attribute transformationMaps entire set of values of given attribute to a new set such that old value can be identified with new value

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Descrição
Data mining FlashCards sobre Data, criado por Johan Isaksson em 23-10-2018.
Criado por
Johan Isaksson
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