Identical particlesIn quantum mechanics, identical particles (also called indistinguishable or indiscernible particles) are particles that cannot be distinguished from one another, even in principle. Species of identical particles include, but are not limited to, elementary particles (such as electrons), composite subatomic particles (such as atomic nuclei), as well as atoms and molecules. Quasiparticles also behave in this way.
Lasso (statistics)In statistics and machine learning, lasso (least absolute shrinkage and selection operator; also Lasso or LASSO) is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model. It was originally introduced in geophysics, and later by Robert Tibshirani, who coined the term. Lasso was originally formulated for linear regression models. This simple case reveals a substantial amount about the estimator.
India inkIndia ink (British English: Indian ink; also Chinese ink) is a simple black or coloured ink once widely used for writing and printing and now more commonly used for drawing and outlining, especially when inking comic books and comic strips. India ink is also used in medical applications. Compared to other inks, such as the iron gall ink previously common in Europe, India ink is noted for its deep, rich black. It is commonly applied with a brush (such as an ink brush) or dip pen.
InkInk is a gel, sol, or solution that contains at least one colorant, such as a dye or pigment, and is used to color a surface to produce an , text, or design. Ink is used for drawing or writing with a pen, brush, reed pen, or quill. Thicker inks, in paste form, are used extensively in letterpress and lithographic printing. Ink can be a complex medium, composed of solvents, pigments, dyes, resins, lubricants, solubilizers, surfactants, particulate matter, fluorescents, and other materials.
Feature selectionFeature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. Stylometry and DNA microarray analysis are two cases where feature selection is used. It should be distinguished from feature extraction. Feature selection techniques are used for several reasons: simplification of models to make them easier to interpret by researchers/users, shorter training times, to avoid the curse of dimensionality, improve data's compatibility with a learning model class, encode inherent symmetries present in the input space.
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