"Discriminate" Natural Recordings by Native Speakers
To distinguish or classify something or someone as belonging to a particular category or group, often in a way that is unfair or biased.
To discretises means to convert a continuous quantity or a continuous data set into a set of discrete values or elements, often by sampling or quantizing the continuous data. It is often used in mathematics, science, and engineering to simplify complex continuous data into manageable discrete pieces.
Discretising refers to the process of converting a continuous signal or a continuous variable into a discrete sequence of values. It is a method used in various fields, such as signal processing, image processing, and numerical analysis, where the continuous data is represented as a set of discrete points or values. The goal of discretising is often to simplify the data, reduce its complexity, or facilitate processing and analysis in a computer or algorithm. Discretising can be performed using various methods, including sampling, quantization, and rounding.
To discretize means to convert a continuous quantity or process into a finite sequence of discrete values or steps. In other words, it involves breaking down a continuous function or concept into a series of distinct, separate points or units, rather than considering it as a continuous whole. This can be done in various fields, such as mathematics, physics, engineering, or computer science, to simplify complex systems, reduce computational complexity, or improve theoretical understanding. In everyday language, discretizing can be thought of as simplifying a fluid or continuous process into a series of separate, distinct items or steps.
The word "discretized" means to convert or represent something, especially a continuous phenomenon or a function, into a form consisting of separated or distinct units or values, such as a mesh or a grid. For example, a geographic region might be discretized into smaller areas or pixels for analysis or mapping. It can also refer to the process of breaking something down into separate or discrete objects, units, or parts, as opposed to viewing it as a continuous or cohesive whole. In computing and mathematics, discretized versions of continuous functions or signals are often used to process or analyze them more efficiently.
Discretizes is a verb that means to convert (a continuous quantity or process) into a sequence of discrete steps or values, often for the purpose of simplification, analysis, or computational modeling. It is the opposite of continuous, where a variable is represented by a smooth curve or a range of values, while a discrete variable can only take on specific, distinct values. For example, discretizing a continuous function like temperature might involve reducing it to a set of specific temperature levels, such as 0°C, 5°C, 10°C, and so on.
Discretizing is the process of converting a continuous variable or a continuous function into a discrete set of values or a discrete function. This is often done to simplify complex mathematical models or to make them more feasible for simulation or calculation. Discretization is used in many fields, including numerical analysis, control theory, and scientific computing. It involves dividing a continuous space or variable into a finite number of discrete points or values, and then approximating the behavior of the system or function at those points. This can help to reduce the computational complexity of a problem, make it easier to analyze or solve, or enable the use of techniques that are only applicable to discrete systems.
The term "discriminant" refers to a value or expression that determines whether a polynomial equation has only one or multiple solutions. In other words, a discriminant is a mathematical formula used to determine the nature of the roots of an equation. It is usually represented as "b^2 - 4ac" in the quadratic formula, where "a", "b", and "c" are coefficients of the polynomial equation. If the discriminant is positive, the equation has two distinct real solutions; if it is zero, the equation has one repeated real solution; and if it is negative, the equation has no real solutions.
Discriminated: Treated or referred to in a unfair or prejudiced way because of a person's race, gender, sexuality, age, or other personal characteristic.
The verb "discriminates" means to treat unfairly or poorly because of a particular characteristic, such as race, gender, age, or disability; to make distinctions or draw lines between groups or individuals based on these characteristics.
Having or showing a tendency to favor or prefer one or a few individuals or groups over others, often resulting in unfair treatment or bias; having a critical and discerning ability to recognize and distinguish between different things, such as qualities, characteristics, or taste.
In a discriminatory or selective manner, showing a tendency to favor or prefer one person or thing over others; having a refined or discerning sense of taste, judgment, or standards.
Discrimination is the unjust or prejudiced treatment of a person or group of people based on their race, gender, age, disability, religion, or other characteristics. It involves making negative distinctions between people based on attributes over which people have no control. Discrimination can take many forms, including denying opportunities, denying access, or denying respect. It can also be subtle, such as making condescending comments or ignoring someone's efforts or achievements.
Having or showing a tendency to judge people or things unfairly because of their race, gender, age, or other non-essential characteristics.
A discriminator is a person or thing that identifies or distinguishes between different things, often in a way that is unfair or biased. In a broader sense, a discriminator can also refer to a function or a system that separates or distinguishes between different classes, categories, or groups. In statistics and data analysis, a discriminator can be a statistical model that predicts the probability of an event or outcome given the features of an individual or a sample. In artificial intelligence and machine learning, a discriminator is often used to distinguish between different classes or labels, such as distinguishing between real and fake data or between different categories of text or images.