Thuật ngữ AI
Từ điển đầy đủ về Trí tuệ nhân tạo
Multiplicative Interaction
Mathematical operation combining two or more variables through multiplication to capture synergistic non-linear effects between them in predictive models.
Additive Interaction
Linear combination of variables where the combined effect equals the sum of individual effects, allowing modeling of cumulative relationships between features.
Feature Crossing
Technique for creating new features by crossing existing variables to reveal hidden patterns and improve machine learning model performance.
Interaction Terms
Synthetic variables created by mathematical combination of existing features to represent interaction effects in statistical and predictive models.
Variable Transformation
Mathematical process applying functions to existing variables to create new representations that improve model linearity and interpretability.
Non-linear Interactions
Complex relationships between variables where the combined effect is not proportional to the sum or product of individual effects, requiring specific transformations.
Feature Interaction Matrix
Matrix structure systematically representing all possible interactions between feature pairs to identify the most informative combinations.
Cross-Feature Generation
Automated process of creating new features by crossing existing variables according to predefined rules to enrich the feature space.
Interaction Depth
Level of complexity of interactions between features, measuring the number of variables combined simultaneously in a given interaction.
Higher-Order Features
Features derived from interactions involving three or more variables, allowing the capture of complex multidimensional relationships in data.
Feature Composition
Systematic method of constructing new features by weighted or unweighted combination of existing variables according to predefined patterns.
Interaction Discovery
Process of automatically identifying the most relevant interactions between variables through statistical or algorithmic analysis to optimize feature engineering.
Feature Augmentation
Extension of the feature space by creating new synthetic variables based on interactions between existing variables to improve modeling.
Synergistic Features
Features created by combining variables exhibiting a synergistic effect, where their interaction produces informative value greater than the sum of their parts.
Feature Interaction Space
Multidimensional mathematical space representing all possible interactions between features, explored to identify optimal combinations.
Interaction Strength
Quantitative measure of the importance and significance of an interaction between variables, often assessed by statistical tests or feature importance.
Feature Pairing
Systematic technique for creating pairwise feature interactions to explore bilateral relationships in datasets.
Multi-way Interactions
Complex interactions involving three or more variables simultaneously, enabling the modeling of multidimensional phenomena in predictive systems.
Interaction Encoding
Process of transforming and representing interactions between variables in numerical form suitable for machine learning algorithms.