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Glosarium AI

Kamus lengkap Kecerdasan Buatan

162
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23.060
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Multiplicative Interaction

Mathematical operation combining two or more variables through multiplication to capture synergistic non-linear effects between them in predictive models.

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Additive Interaction

Linear combination of variables where the combined effect equals the sum of individual effects, allowing modeling of cumulative relationships between features.

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Feature Crossing

Technique for creating new features by crossing existing variables to reveal hidden patterns and improve machine learning model performance.

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Interaction Terms

Synthetic variables created by mathematical combination of existing features to represent interaction effects in statistical and predictive models.

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Variable Transformation

Mathematical process applying functions to existing variables to create new representations that improve model linearity and interpretability.

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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.

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Feature Interaction Matrix

Matrix structure systematically representing all possible interactions between feature pairs to identify the most informative combinations.

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Cross-Feature Generation

Automated process of creating new features by crossing existing variables according to predefined rules to enrich the feature space.

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Interaction Depth

Level of complexity of interactions between features, measuring the number of variables combined simultaneously in a given interaction.

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Higher-Order Features

Features derived from interactions involving three or more variables, allowing the capture of complex multidimensional relationships in data.

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Feature Composition

Systematic method of constructing new features by weighted or unweighted combination of existing variables according to predefined patterns.

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Interaction Discovery

Process of automatically identifying the most relevant interactions between variables through statistical or algorithmic analysis to optimize feature engineering.

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Feature Augmentation

Extension of the feature space by creating new synthetic variables based on interactions between existing variables to improve modeling.

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Synergistic Features

Features created by combining variables exhibiting a synergistic effect, where their interaction produces informative value greater than the sum of their parts.

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Feature Interaction Space

Multidimensional mathematical space representing all possible interactions between features, explored to identify optimal combinations.

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Interaction Strength

Quantitative measure of the importance and significance of an interaction between variables, often assessed by statistical tests or feature importance.

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Feature Pairing

Systematic technique for creating pairwise feature interactions to explore bilateral relationships in datasets.

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Multi-way Interactions

Complex interactions involving three or more variables simultaneously, enabling the modeling of multidimensional phenomena in predictive systems.

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Interaction Encoding

Process of transforming and representing interactions between variables in numerical form suitable for machine learning algorithms.

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