supervised methods

USAGE SUMMARY

The phrase "supervised methods" is correct and usable in written English.
It is typically used in the context of machine learning or statistics to refer to techniques that require labeled training data. Example: "In our research, we focused on supervised methods to improve the accuracy of our predictive models."

✓ Grammatically correct

Science

Academia

Human-verified examples from authoritative sources

Exact Expressions

56 human-written examples

Broad-coverage relation extraction either requires expensive supervised training data, or suffers from noise introduced by distantly supervised methods.

Stanford University

S.D. and C.F supervised methods development.

Nature

However, the class label information plays such an important role that it confines supervised methods by defining the possible classes.

Stanford University

In addition, GNDE and KGNDE are supervised methods.

EURASIP Journal on Advances in Signal Processing

Supervised methods train linear or nonlinear classifiers based on labeled pixels or blocks.

EURASIP Journal on Advances in Signal Processing

Supervised methods assume that there are examples of insider threats available for building a classification tool.

Security Informatics

Supervised methods consider the class information, whereas unsupervised ones do not consider the class information.

Human-centric Computing and Information Sciences

Human-verified similar examples from authoritative sources

Similar Expressions

4 human-written examples

We'll also find ways of using semi-supervised methods.

Columbia University

Semi-supervised methods combine these two approaches, leveraging patterns in unlabelled data to improve power in the prediction of labels.

Nature

We compare our approach with state of the art semi-supervised methods.

Pattern Recognition Letters

Covering 190 publications, we give an overview of broad segmentation topics including not only the classic unsupervised methods, but also the recent weakly-/semi-supervised methods and the fully-supervised methods.

Journal of Visual Communication and Image Representation

Expert writing Tips

Best practice

When discussing machine learning, clearly specify the type of "supervised methods" you are using (e.g., classification, regression) to provide context and avoid ambiguity.

Common error

Avoid using "supervised methods" as a blanket term without specifying the specific algorithm or technique employed. This can lead to confusion and a lack of clarity in your writing.

Linguistic Context

The phrase "supervised methods" functions as a noun phrase, typically used to describe a category of machine learning or statistical techniques. Ludwig AI confirms its grammatical correctness. It often acts as the subject or object of a sentence when discussing data analysis or model building.

Expression frequency: Common

Frequent in

Science

62%

Academia

33%

Formal & Business

4%

Less common in

News & Media

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "supervised methods" is a grammatically sound and commonly used noun phrase in the realms of machine learning and statistics. Ludwig AI confirms its broad applicability in scientific and academic contexts, where it serves to categorize techniques that rely on labeled data for training. To avoid ambiguity, specify the exact algorithm or technique you are using, such as classification or regression. While versatile, remember its primary function is to distinguish it from "unsupervised methods", which operate on unlabeled data.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

supervised learning techniques

Focuses on the learning aspect rather than the general methodology.

supervised algorithms

Specifically refers to the algorithms used in supervised learning.

labeled learning approaches

Emphasizes the use of labeled data in the learning process.

guided learning strategies

Highlights the guidance provided by the labeled data.

training-based methods

Focuses on the training aspect of these methods.

classification algorithms

Highlights the use for classifying data.

regression algorithms

Highlights the use for regression tasks.

supervised machine learning

Specifically refers to the field of machine learning.

discriminative learning

Focuses on the methods that discriminate between different classes.

supervised statistical methods

Highlights the statistical nature of these methods.

FAQs

How do I use "supervised methods" in a sentence?

You can use "supervised methods" to describe machine learning techniques that require labeled training data. For example: "We employed several "supervised methods" to classify the images."

What is the difference between "supervised methods" and "unsupervised methods"?

"Supervised methods" require labeled data for training, while "unsupervised methods" do not. Supervised learning aims to predict outcomes based on known input-output pairs, whereas unsupervised learning seeks to find patterns in unlabeled data.

What are some examples of "supervised methods"?

Examples of "supervised methods" include linear regression, logistic regression, support vector machines (SVMs), and decision trees.

When should I use "supervised methods" over other machine learning approaches?

Use "supervised methods" when you have a labeled dataset and a clear target variable that you want to predict or classify.