build a predictive model

USAGE SUMMARY

"build a predictive model" is a correct and usable phrase in written English and can be used in many different contexts.
For example, "The data scientist has been tasked to build a predictive model to forecast future demand."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

To determine the role of EEG and BAEPs to predict the outcome and to build a predictive model in patients suffering from severe head injury (SHJ).

Critical Care

This ranking can be used to build a predictive model, without eliminating any variables, using any other machine learning prediction method, in this case and differently from Genuer et al [43], Support Vector Machines [48], inserting the variables stepwise in order to find a good balance between the number of variables and prediction error.

Journal of Cheminformatics

Using this and a series of external "clues" — news that could affect stock price movements — the players build a predictive model.

The New York Times

to build a predictive model or to measure tie strength.

Journal of the Brazilian Computer Society

The secondary goal was to build a predictive model based on identified risk factors.

European Journal of Obstetrics & Gynecology and Reproductive Biology

After data preparation, the next important task is fitting an appropriate machine learning algorithm to build a predictive model.

Journal of Cheminformatics

After exploratory analysis, 29 were selected to build a predictive model of human fire ignition using logistic regression analysis.

Journal of Environmental Management

In order to build a predictive model, the curing process should be studied with modelling and experiments.

Composite Structures

Further studies are required to understand future responses to post-fire changes and to build a predictive model for different burned forest environments.

Ecological Processes

To build a predictive model, the Parzen-Rosenblatt Window method [18] was used as the basis of a multi-class classification algorithm.

Journal of Cheminformatics

Using a large longitudinal mobile phone database we build a predictive model of tie persistence based on intensity, intimacy, structural and temporal patterns of social interaction.

EPJ Data Science

Expert writing Tips

Best practice

When using "build a predictive model", clearly define the input variables and the desired outcome to ensure the model's relevance and accuracy.

Common error

Avoid overfitting your predictive model by using an appropriate amount of data and cross-validation techniques. Overfitting can lead to high accuracy on the training data but poor performance on new, unseen data.

Linguistic Context

The phrase "build a predictive model" functions as a verbal phrase often used as part of a larger sentence to describe an action or goal. Ludwig AI confirms its common use. Example: "The goal was to build a predictive model based on identified risk factors."

Expression frequency: Very common

Frequent in

Science

75%

News & Media

15%

Formal & Business

10%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "build a predictive model" is a grammatically sound and frequently used expression, as verified by Ludwig AI. It predominantly appears in formal and scientific contexts, denoting the creation of a forecasting tool or analytical framework. While alternatives like "develop a predictive model" or "create a forecasting model" exist, they offer nuanced differences in emphasis. When employing this phrase, it's crucial to ensure a clear definition of input variables and desired outcomes to maximize model accuracy and relevance. Be aware of overfitting, which can significantly impair the model's performance on unseen data. In essence, "build a predictive model" is a versatile phrase best suited for technical discussions and analytical reports within scientific, academic, and business domains.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

develop a predictive model

Replaces "build" with "develop", emphasizing the progressive aspect of creating the model.

create a forecasting model

Substitutes "predictive" with "forecasting", highlighting the model's purpose to forecast.

construct a predictive algorithm

Replaces "model" with "algorithm", focusing on the computational aspect.

design a predictive system

Substitutes "model" with "system", broadening the scope to include the entire predictive framework.

establish a predictive framework

Changes "build a model" to "establish a framework", emphasizing the foundation for prediction.

formulate a predictive model

Replaces "build" with "formulate", stressing the intellectual creation of the model.

implement a predictive model

Focuses on the implementation aspect rather than the creation.

engineer a predictive solution

Highlights the problem-solving aspect of creating a predictive tool.

generate a predictive capability

Shifts the focus to the resulting capability rather than the model itself.

assemble a predictive tool

Replaces "build" with "assemble", suggesting a combination of existing components.

FAQs

How can I use "build a predictive model" in a sentence?

You can use "build a predictive model" to describe the process of creating a statistical model to forecast future outcomes. For example, "The company aims to build a predictive model to anticipate customer churn."

What's the difference between "build a predictive model" and "develop a predictive model"?

While both phrases are similar, "build a predictive model" generally refers to the initial construction, whereas "develop a predictive model" can encompass ongoing refinement and improvement.

What are the key steps to build a predictive model?

The key steps typically include data collection, data preprocessing, feature selection, model training, model evaluation, and model deployment.

Which machine learning algorithms are commonly used to build a predictive model?

Common algorithms include linear regression, logistic regression, decision trees, support vector machines, and neural networks, depending on the nature of the data and the prediction task.