input vector

USAGE SUMMARY

The phrase "input vector" is correct and usable in written English.
It is typically used in technical or scientific contexts, particularly in fields such as computer science, statistics, and mathematics. Example: "The machine learning algorithm requires an input vector of numerical values in order to make accurate predictions."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

U or U z) : Control input vector.

EURASIP Journal on Information Security

is a constant external input vector.

Journal of Inequalities and Applications

Pad the input vector with zero dimensions.

EURASIP Journal on Audio, Speech, and Music Processing

Generalized input vector containing rail displacements.

Urban Rail Transit

(x_{i}) are called input vector.

Vietnam Journal of Computer Science

At each node, these weighted input vector components are added.

Advances in Space Research

The new input vector also needs to be calculated.

EURASIP Journal on Advances in Signal Processing

Each input vector has a number of features.

Vietnam Journal of Computer Science

U ∗ or U ∗ z) : Optimal control input vector.

EURASIP Journal on Information Security

This FV is considered an input vector for the classifier.

EURASIP Journal on Advances in Signal Processing

The reduced input vector (the vector that includes components of the input vector appearing in the first subsystem) is designed to asymptotically stabilize the first subsystem.

ISA Transactions

Expert writing Tips

Best practice

When defining an "input vector", clearly specify the data types and range of values it can contain to ensure compatibility with the processing algorithm.

Common error

Avoid assuming all components of the "input vector" are equally important. Perform feature selection to identify and prioritize the most relevant features, improving model performance and reducing computational cost.

Linguistic Context

The phrase "input vector" functions primarily as a noun phrase, typically acting as the subject or object in a sentence within scientific and technical contexts. As Ludwig AI confirms, it is widely accepted in written English. Examples show it represents a set of data points used for processing or analysis.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Encyclopedias

0%

Ludwig's WRAP-UP

The term "input vector" is a grammatically sound and widely used noun phrase, primarily within scientific and technical domains. As noted by Ludwig AI, it is considered correct and suitable for formal writing. The phrase serves to define a structured set of data points, functioning as input for various systems and algorithms. Its usage is predominantly formal, reflecting its prevalence in academic and research contexts. Common related phrases include "feature vector" and "data vector", offering alternative ways to express the same concept with slight nuances. Best practices for using "input vector" involve clearly specifying data types and ranges, while common errors include neglecting feature selection. This wrap-up summarizes the key linguistic and technical aspects of the phrase, providing a comprehensive understanding of its usage and context.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

feature vector

Focuses specifically on the vector containing features or attributes of a data point.

data vector

Emphasizes the vector as a representation of data.

attribute vector

Highlights the vector's role in representing attributes.

signal vector

Used when the vector represents a signal.

parameter vector

Specifically for vectors containing parameters of a model or system.

observation vector

Focuses on the vector as a collection of observations.

input array

Uses "array" instead of "vector", implying a multi-dimensional structure.

input data series

Emphasizes the sequential nature of the input.

stimulus vector

Highlights the vector's role as a stimulus in a system.

predictor vector

Focuses on the vector's use in prediction models.

FAQs

How is an "input vector" used in machine learning?

In machine learning, an "input vector" represents a single instance of data fed into a model. Each element of the vector corresponds to a feature or attribute of the data point, enabling the model to learn patterns and make predictions.

What is the difference between an "input vector" and a feature matrix?

An "input vector" represents a single data point, while a feature matrix is a collection of multiple "input vectors", where each row corresponds to a different data point and each column represents a feature.

How do I determine the appropriate size for my "input vector"?

The size of the "input vector" should match the number of features or attributes relevant to your problem. Feature selection techniques can help reduce the dimensionality of the "input vector" by identifying and removing redundant or irrelevant features.

What are some alternatives to calling something an "input vector"?

Depending on the context, you can use alternatives like "feature vector", "data vector", or "parameter vector" to describe the "input vector".