Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Factor Outlier Local

U turjun LOF sida saamiga cufnaanta maxalliga ah oo kala saar fogaanta caalamiga ah, oo ay ku jiraan cabbirka deriska iyo nooca-cusub.

Wadooyinka haga ee la xidhiidhaQodobka Outlier Local
Su'aal 1 ee 8

What does an LOF score substantially above one suggest?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. What does an LOF score substantially above one suggest?
    • The point is less dense than its local neighbors
    • The point is equally dense as its local neighbors
    • It is far from the global center even if its neighborhood is dense
    • The score is a calibrated anomaly probability
  2. Why can a far-away point receive an ordinary LOF score?
    • LOF ignores all neighbor information
    • It may belong to a separate dense subgroup with similar local density
    • Distance is always set to zero outside the main cloud
    • LOF measures only the global mean
  3. What does increasing the neighbor count generally change?
    • The number of features used in the density ratio
    • The sign convention of the returned score
    • The scale over which local density is compared
    • The global clustering method used before LOF
  4. Why does feature scaling matter for LOF?
    • It changes local density into a Gaussian parameter
    • It guarantees every feature contributes equally without preprocessing
    • It changes neighbor count into a class label
    • Nearest-neighbor distances depend on feature units
  5. How does novelty detection differ from fitted-sample outlier detection?
    • It requires labels for every training sample
    • It scores new observations against a reference fit
    • It retrains a new density for each query
    • It reports only global cluster means
  6. In scikit-learn novelty mode, what should users avoid according to its documentation?
    • Checking neighbor count
    • Scaling numeric predictors
    • Using novelty scoring methods on the training set
    • Scoring new unseen cases
  7. Which pattern indicates a local rather than global anomaly concept?
    • Distance from the global center is large even when local density is high
    • The observation has a rare category label
    • The global cluster contains few observations
    • Density is low relative to nearby points
  8. Why check the sign convention of an LOF API score?
    • Libraries may invert scores so stronger outliers have lower numeric values
    • The sign determines how many neighbors exist
    • LOF scores are always probabilities
    • The score direction is identical in every implementation