reduction$67963$ - translation to ελληνικό
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Μετάφραση και ανάλυση λέξεων από την τεχνητή νοημοσύνη ChatGPT

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  • πώς χρησιμοποιείται η λέξη
  • συχνότητα χρήσης
  • χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
  • επιλογές μετάφρασης λέξεων
  • παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
  • ετυμολογία

reduction$67963$ - translation to ελληνικό

PROCESS OF REDUCING THE NUMBER OF RANDOM VARIABLES UNDER CONSIDERATION
Dimension reduction; Dimensionality Reduction; Dimensionality reduction algorithm; Linear dimensionality reduction
  • A visual depiction of the resulting LDA projection for a set of 2D points.
  • A visual depiction of the resulting PCA projection for a set of 2D points.

reduction      
n. ελάττωση, έκπτωση, μείωση, μετατροπή, υποβίβαση, αναγωγή
reduction of capital         
STOCK VALUE DECREASE OF A COMPANY
Capital reduction; Reduction of the capital; Reduction of capital stock
μείωση κεφαλαίου
reductio ad absurdum         
  • alt=A bearded white Christian cleric in red argues towards an older pensive white Christian cleric in black.
FORM OF ARGUMENT IN INFORMAL LOGIC
Reductio ad absurdam; Reductio Ad Absurdum; Incoherency argument; Reduction ad absurdum; Ad absurdum; Indirect argument; Road Runner Tactic; Apagogical argument; Reductio ab absurdo; Reductio ad absurdium; Argumentum ad absurdum; Reductio ad absurdem; Reducio ad absurdum; Assume by contradiction; Reduction to absurdity; Reduction ad absurbum; Argument ad absurdum; Reducto ad absurdum; Absurd argument; Reductio ad Absurdum
εις άτοπο απαγωγή

Ορισμός

reduce
v.
1) (D; tr.) to reduce in (he was reduced in rank)
2) (d; tr.) to reduce to (she was reduced to poverty; the corporal was reduced to the rank of private)

Βικιπαίδεια

Dimensionality reduction

Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can be undesirable for many reasons; raw data are often sparse as a consequence of the curse of dimensionality, and analyzing the data is usually computationally intractable (hard to control or deal with). Dimensionality reduction is common in fields that deal with large numbers of observations and/or large numbers of variables, such as signal processing, speech recognition, neuroinformatics, and bioinformatics.

Methods are commonly divided into linear and nonlinear approaches. Approaches can also be divided into feature selection and feature extraction. Dimensionality reduction can be used for noise reduction, data visualization, cluster analysis, or as an intermediate step to facilitate other analyses.