AN APPROACH TO FEATURE SPACE FORMATION FOR MACHINE LEARNING MODELS

Matchonov, Shohruh, Asatov, Timur

Techscience.uz - техника фанлари долзарб масалалри · 2025-yil

Annotatsiya

In this study, various approaches to feature space formation for solving data processing tasks are examined, and their implementation mechanisms in a programming environment are investigated. The paper describes methods for establishing internal relationships based on data characteristics, categorizing information, and handling categorical variables. Furthermore, techniques for grouping, scaling, and normalizing numerical data are presented, including practical approaches to data preprocessing in software environments.

Maqola ma’lumotlari
MualliflarMatchonov, Shohruh, Asatov, Timur
JurnalTechscience.uz - техника фанлари долзарб масалалри
Nashr sanasi2025-10-23
Jild3
Son9
Betlar8-13
TilO‘zbek
DOI10.47390/ts-v3i9y2025no2

Kalit so‘zlar

One-Hot Encoding, Label Encoding, Binning, Empirical Rule, MinMax Normalization, z-Normalization, StandardScaler, Normalization, Scaling., One-Hot Encoding, Label Encoding, Binning, Empirik qoida, MinMax normallashtirish, z-normallashtirish, StandardScaler, Normallashtirish, Masshtablash.

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