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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

162
categorie
2.032
sottocategorie
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Scatter Plot

Scatter plot visualizing the relationship between two quantitative variables using points positioned according to their coordinates. Allows identification of trends, correlations, and outliers in bivariate data.

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Box Plot

Box plot showing the statistical distribution of a variable through five indicators: minimum, first quartile, median, third quartile, and maximum. Excellent for comparing distributions between multiple groups.

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Heatmap

Heatmap using colors to represent the intensity of values in a two-dimensional matrix. Particularly effective for visualizing correlations and patterns in tabular data.

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Violin Plot

Combination of a box plot and a density plot showing the distribution of a variable through its flared shape. The width represents the density of data at different values.

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Pair Plot

Matrix of scatter plots simultaneously showing the relationships between all pairs of variables in a dataset. The diagonal often presents the univariate distributions of each variable.

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Treemap

Hierarchical visualization using nested rectangles to represent proportions and data structures. The size of each rectangle is proportional to its numerical value.

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Density Plot

Smoothed graphical representation of the distribution of a continuous variable using kernel density estimation. An alternative to the histogram offering a continuous view of the distribution.

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Bubble Chart

Variation of the scatter plot where the size of the bubbles represents a third quantitative dimension. Allows simultaneous visualization of three variables in a two-dimensional space.

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Radar Chart

Star-shaped graph allowing comparison of several quantitative variables on radial axes emanating from a central point. Useful for evaluating multivariate profiles and relative performances.

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Violin Plot

Extension of the box plot combining distribution symmetry and density estimation to visualize the complete shape of data. Particularly useful for comparing distributions between categories.

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Joint Plot

Combination of a central scatter plot with marginal distributions on the axes. Provides a complete view of the bivariate relationship and individual distributions simultaneously.

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Swarm Plot

Categorical graph dispersing individual points along the categorical axis to avoid overlaps. Allows visualization of the actual distribution of observations without aggregation.

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Contour Plot

Three-dimensional representation on a 2D plane using contour lines to connect points of equal value. Particularly effective for visualizing response surfaces and density functions.

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Hexbin Plot

Alternative to scatter plot for very dense data using hexagons to aggregate points. The color of each hexagon represents the number of points contained in that region.

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Parallel Coordinates

Multidimensional visualization technique using parallel axes to represent multiple dimensions. Each line represents an observation crossing all variable axes.

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Q-Q Plot

Quantile-quantile plot comparing the distribution of a sample to a theoretical distribution. Points aligned on a diagonal line indicate adequacy between the distributions.

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