Additive logistic models. Medical search. Frequent questions

The paper was co-authored by Thom Hodgson, Michael Kay and Russel King of NC State's Fitts Department and the Center for Additive Manufacturing and Logistics. (ncsu.edu)

The interaction between nitrous oxide and sevoflurane was investigated using logistic regression analysis of the responses to intubation. (asahq.org)

Compared to the elderly without pRBD or sleep insufficiency, pRBD and sleep insufficiency was each associated with a 2.57-fold (OR = 2.57, 95%CI: 1.46-4.31) and 1.45-fold (OR = 1.45, 95%CI: 1.11-1.88) risk of falls individually, while their coexistence was associated with a less-than-additive 17% (OR = 1.17, 95%CI: 0.43-2.63) increased risk of falls. (biomedcentral.com)
In contrast with these findings, other studies have reported that the contribution of nitrous oxide to the MAC of sevoflurane 6 and desflurane 7 is less than additive. (asahq.org)

Multivariate logistic regression analysis showed that using either ST depression. (who.int)
The association between AST / ALT and peripheral arterial disease (PAD), which was defined as ABI ≤ 0.9 in either leg, was estimated by a multivariate logistic regression model. (researchsquare.com)
Odds ratio (ORs) and 95% confidence intervals (CIs) were estimated using multivariate logistic regression models. (biomedcentral.com)
For multivariate statistical analysis, it estimated the impact of sociodemographic and health variables on stress by linear regression, and on distress with logistic regression. (bvsalud.org)

An increase in the number of publicly available genomes of influenza A across all hosts and subtypes has motivated an expanding literature on the algorithmic detection and classification of reassortant viruses [ 20 - 27 ], through phylogenetic analysis or via statistical models of genetic distance. (biomedcentral.com)
We show that this seemingly mysterious phenomenon can be understood in terms of well-known statistical principles, namely additive modeling and maximum likelihood. (projecteuclid.org)
Friedman et al's paper "Additive logistic regression: a statistical view of boosting" offers an explanation. (stackexchange.com)

However, C5.0's boosting is somewhat different from AdaBoost, e.g. additive rather than multiplicative weight adjustment of misclassified cases, with the goal of improving performance in the presence of moderate noise. (stackexchange.com)
Multiplicative and additive interactions between pRBD and sleep insufficiency were examined using likelihood ratio tests and relative excess risk due to interaction (RERI), respectively. (biomedcentral.com)
The combination of these two factors demonstrated evidence of a negative interaction on both multiplicative (ratio of ORs = 0.31, 95%CI: 0.10, 0.86) and additive (RERI = − 1.85, 95%CI: − 3.61, − 0.09) scale. (biomedcentral.com)
Multivariable logistic regression models were used for joint effect and interaction analyses on the multiplicative and additive scales. (qub.ac.uk)

Genetic associations with ILD were assessed in logistic regression models overall and in subgroups defined by race and smoking status, with additive interactions assessed by the relative excess risk of interaction (RERI). (cdc.gov)
Additive interactions between MUC5B-race and MUC5B-smoking were not statistically significant. (cdc.gov)
Lack of Automatic Feature Interaction − Logistic regression assumes that the relationship between features and the target variable is additive, neglecting potential interactions between features. (tutorialspoint.com)
Introduction aux principaux concepts en biologie : origine et chimie de la vie, capture et utilisation de l'énergie dans les systèmes biologiques, hérédité et génétique, biodiversité et ses origines, évolution, systématique des principaux groupes d'organismes vivants et interactions biotiques. (uottawa.ca)

Specifically, if one considers AdaBoost as a generalized additive model and then applies the cost function of logistic regression, one can derive the LogitBoost algorithm. (wikipedia.org)

The model's journey started as an order from Carderock's Fabrication and Technical Support (F&TS) Division, where technicians, such as Adam Smith and Ryan Franke of the Subtractive and Additive Manufacturing Branch, constructed the model through 3D printing and other processes. (navy.mil)
Another benefit to using additive manufacturing capabilities in constructing models is that it saves time, according to Ship Model Conservator Brian Potter. (navy.mil)
It took a few days to complete, but if I had to make the model from scratch without the additive manufacturing group it would have taken more than a month. (navy.mil)

Famous examples of such explainers are Local Interpretable Model-agnostic Explanations ( LIME ) and SHapley Additive exPlanations ( SHAP ). (kdnuggets.com)
For example, consider your input data has 4 features (x1, x2, x3, x4) and the output of a model is 75, using Shapley values, you can say that feature x1 contributed 30, feature x2 contributed 20, feature x3 contributed -15, and feature x4 contributed 40. (kdnuggets.com)
The sum of these 4 Shapley values is 30+20-15+40=75, i.e., the output of your model. (kdnuggets.com)
For a general model, the time taken to compute Shapley values is exponential to the number of features . (kdnuggets.com)
To be fair, if your model consists of trees, there are faster approximations to compute Shapley values, but it can still be slow. (kdnuggets.com)
The Shapley additive explanations (SHAP) value was applied to explain the influence of the features on model prediction. (biomedcentral.com)

For common genetic variants, early genome-wide association studies (GWASs) found that additive models captured most genotype-phenotype associations, including those with non-additive (also called dominance) effects 17 . (nature.com)

The coefficients in logistic regression just aren't a good measure of the importance of the feature (although they can be an indication if the features are scaled), it is preferable to use other metrics like comparing likelihoods when omitting the features. (stackexchange.com)
Interpretability − The coefficients within logistic regression offer valuable insights into how different features influence the final outcome. (tutorialspoint.com)
Feature selection − Logistic regression can assist in identifying the most influential features by examining the magnitude and significance of the coefficients. (tutorialspoint.com)

On the other hand, XAI is a set of processes and methods that allows users to understand and trust the results/output created by a machine learning model/algorithm. (kdnuggets.com)

Hierarchical logistic regression analyses examined the relative contribution of current DSM-IV WTC- PTSD and LRS to impairments, adjusting for demographic, exposure, and health risk factors. (cdc.gov)

To scan the historical number of porcine submissions received at ISU VDL each month, and to forecast the expected number of porcine submissions to be made each month for the coming year, an additive Winters model with logistic transformation was used. (swineweb.com)

We describe a framework, ExplainD, for explaining decisions made by classifiers that use additive evidence. (aaai.org)
We demonstrate our ExplainD framework using implementations of naïve Bayes, linear support vector machine, and logistic regression classifiers on example applications. (aaai.org)
Indeed, nothing prevents the inclusion or exclusion of a variable with a small effect size from having a large effect on predictive accuracy even within the framework of logistic regression, especially if there are strong confounding or mediation effects of that variable on other predictors, and including those confounding or mediation effects leads to better predictions. (stackexchange.com)
Multi-state models, as an extension of traditional models in survival analysis, have proved to be a flexible framework for analysing the transitions between various states of sickness absence and work over time. (biomedcentral.com)

Applications to survival models and binary outcome models are illustrated. (nih.gov)
Since there is limited data, simple regression model and binary regression model failed to generate satisfactory results, so an additive periodic time series model was built to forecast business orders and income. (hindawi.com)
Build two linked models, where the first one predicts the binary event while the second one predicts the amount (Automate RELATED). (additive-net.de)
I'm trying to model a binary classification problem. (stackexchange.com)
Versatility − Logistic regression can handle both binary and multi-class classification problems, providing flexibility in various scenarios. (tutorialspoint.com)

Despite the fact that many machine learning models are black boxes, understanding the rationale behind the model's predictions would certainly help users decide when to trust or not to trust their predictions. (kdnuggets.com)
LIME explains the predictions of any classifier in an interpretable and faithful manner by learning an interpretable model locally around the prediction. (kdnuggets.com)
While highly accurate, neural networks suffer from a lack of interpretability-it is difficult to identify the model components that lead to specific predictions. (kdnuggets.com)

The RNN models have excellent predictive performance for predicting EF risk and have potential to become real-time assistant decision-making systems for extubation. (biomedcentral.com)

This study aims to develop and validate interpretable recurrent neural network (RNN) models for dynamically predicting EF risk. (biomedcentral.com)

Data Binning Analysis Engine bins variables using model-based binning (via AUTOMATE BIN), or using weights of evidence coding. (additive-net.de)
2016. A New Method for Elicitation of Criteria Weights in Additive Models: Flexible and Interactive Tradeoff. (scielo.br)

2003. A case study of supplier selection for lean supply by using a mathematical model. (scielo.br)
The BLM is a mathematical model developed to measure, assess, and understand how the chemical properties of a waterbody can affect metallic contaminant speciation, bioavailability, and consequent toxicity, comprising an important tool in understanding and predicting metal toxicity in different waterbodies [8,10]. (researchgate.net)

When it comes to the field of machine learning and artificial intelligence, classification models hold immense significance in deciphering extensive volumes of data. (tutorialspoint.com)

These results can be used for building (1) simpler models, which require data only from aerobiological monitoring sites, and (2) combined meteorological and aerobiological models for predicting high levels of pollen concentration. (springer.com)
Although both of the models produced satisfactory results and showed very nearly the same of goodness-of-fit in the sample, the logistic model presented better forecasting performance out of the sample therefore closer to the reality. (hindawi.com)
Patented extensions to the CART modeling engine are specifically designed to enhance results for market research and web analytics. (additive-net.de)
Areas where the MARS engine has exhibited very high-performance results include forecasting electricity demand for power generating companies, relating customer satisfaction scores to the engineering specifications of products, and presence/absence modeling in geographical information systems (GIS). (additive-net.de)
Moreover, SDRS data of cases submitted from Iowa was monitored using a cyclic regression model for weekly proportion of PCR-positive cases, and to forecast the expected upcoming weekly results for Porcine Reproductive Respiratory Syndrome Virus (PRRSV), Porcine Epidemic Diarrhea Virus (PEDV), Porcine Deltacoronavirus (PDCoV) and Mycoplasma hyopneumoniae (MHP). (swineweb.com)
Interpreting conflicting results from Random Forest & Logistic Regression? (stackexchange.com)

To make this regularized learning process sufficiently fast for large scale problems, grafting operates in an incremental iterative fashion, gradually building up a feature set while training a predictor model using gradient descent. (jmlr.org)
At each iteration, a fast gradient-based heuristic is used to quickly assess which feature is most likely to improve the existing model, that feature is then added to the model, and the model is incrementally optimized using gradient descent. (jmlr.org)
Among the non-temporal models, only the random forest (RF) (AUROC: 0.820) and the extreme gradient boosting (XGB) model (AUROC: 0.823) were comparable to the RNN models, but their calibration was deviated. (biomedcentral.com)
Scalability − Logistic regression can be applied to large datasets by utilizing techniques such as stochastic gradient descent, enabling efficient analysis of extensive data collections. (tutorialspoint.com)

Grafting can be used with a variety of predictor model classes, both linear and non-linear, and can be used for both classification and regression. (jmlr.org)
Experiments are reported here on a variant of grafting for classification, using both linear and non-linear models, and using a logistic regression-inspired loss function. (jmlr.org)
ExplainD applies to many widely used classifiers, including linear discriminants and many additive models. (aaai.org)
Associations between infectious SARS-CoV-2 individuals and infection risk were quantified using logistic, generalised additive and linear mixed models. (ox.ac.uk)
Nothing prevents a variable with a small linear effect size as estimated in a logistic regression model from having high importance in a random forest fit. (stackexchange.com)
In modeling by linear and logistic regression, to smoke and female sex have been additive impact on stress. (bvsalud.org)
It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. (ncsu.edu)
Multivariable linear regression models determined the extent to which anthocyanin intake and physical activity predicted lipid parameters. (qub.ac.uk)
Limited Expressiveness − Logistic regression may encounter difficulties in accurately capturing the underlying patterns in datasets that possess non-linear decision boundaries. (tutorialspoint.com)
We conclude that nitrous oxide and sevoflurane suppress the responses to tracheal intubation in a linear and additive fashion in children. (asahq.org)
Several studies have demonstrated that nitrous oxide decreases the minimum alveolar concentration (MAC) of the halogenated anesthetics halothane, 1,2 isoflurane, 3,4 and sevoflurane 5 in a linear additive manner. (asahq.org)

For the two-class problem, boosting can be viewed as an approximation to additive modeling on the logistic scale using maximum Bernoulli likelihood as a criterion. (projecteuclid.org)

Methods for causal inference can provide the needed tools for going from covariate specific estimates to population average effects in multi-state models, and identify causal parameters with a straightforward interpretation based on interventions. (biomedcentral.com)

Since the transportation market is segmented by business type and transportation distance, a polynomial model and logistic curve model were constructed to forecast the growth trend of each segmented transportation market, and the seasonal influence function was fitted by seasonal ratio method. (hindawi.com)

The interaction coefficient between nitrous oxide and sevoflurane did not differ significantly from zero (P = 0.89) and was removed from the logistic model. (asahq.org)

Efficiency − Logistic regression exhibits strong performance when dealing with small datasets and has relatively minimal computational burden, allowing for faster processing times. (tutorialspoint.com)

In this tutorial, we will see an example of how a Generative Additive Model (GAM) is used, learn how functions in a GAM are identified through backfitting, and learn how to validate a time series model. (kdnuggets.com)
Functions allow us to model more complex patterns, and they can be averaged to obtain smoothed curves that are more generalizable. (kdnuggets.com)

Finally the relationship between grafting, stagewise additive modelling, and boosting is explored. (jmlr.org)
Here, we review some techniques in the field of Explainable AI (XAI), why explainability is important, example models of explainable AI using LIME and SHAP, and demonstrate how Explainable Boosting Machines (EBMs) can make explainability even easier. (kdnuggets.com)
The TreeNet modeling engine adds the advantage of a degree of accuracy usually not attainable by a single model or by ensembles such as bagging or conventional boosting. (additive-net.de)

Based on the National Health Interview Survey (NHIS) for the year 2010, a logistic regression model was run to assess the predictors of ER visits in elderly population. (cdc.gov)
17 ] built multilayer perceptron (MLP) neural network model for predicting the outcome of extubation among patients in ICU, and showed that MLP outperformed conventional predictors including RSBI, maximum inspiratory and expiratory pressure. (biomedcentral.com)

The aim of the study was to create and evaluate models for predicting high levels of daily pollen concentration of Corylus , Alnus , and Betula using a spatiotemporal correlation of pollen count. (springer.com)
Other areas of interest include the application of models to evaluate competing configurations of services. (exeter.ac.uk)
During recent years, the biotic ligand model (BLM) has been proposed as a tool to evaluate quantitatively the manner in which water chemistry affects the speciation and biological availability of metals in aquatic systems. (researchgate.net)
however, models to date have not incorporated the ability to evaluate co-exposures with carbon monoxide. (cdc.gov)

With this dataset, you can create your own expected goals model to predict the shot outcome given relevant features. (scorenetwork.org)
Build a classification model to predict the outcome based on the spatial x,y coordinates of the shot. (scorenetwork.org)
That's a great question because although we don't know all the mechanisms that probably lead to the chronic benefits, for acute efficacy, we looked at the benefits across diuresis, natriuresis, and diuretic response, looking for any additive benefit acutely for a diuretic decongestive outcome and then safety across all the other outcomes. (medscape.com)

A USS District of Columbia model sits inside its glass casing at Naval Surface Warfare Center, Carderock Division's Curator of Navy Ship Models Shop in West Bethesda, Md., before delivery to the Washington Naval Yard on Aug. 1, 2022. (navy.mil)
WEST BETHESDA, Md. - A ship model of USS District of Columbia (SSBN 826), built by Naval Surface Warfare Center (NSWC), Carderock Division's Curator of Navy Ship Models, was sent to the Secretary of the Navy's office at the Washington Navy Yard in Washington, D.C., in August 2022. (navy.mil)

One of aerobiology's objectives is to develop models enabling the prediction of pollen concentration in the air (Rodriguez-Rajo et al. (springer.com)
In such a situation, a more precise prediction model is needed to assist clinicians to make the decision of extubation. (biomedcentral.com)
This work develops a novel lightning data assimilation (LDA) technique to make use of Meteosat Third Generation (MTG) Lightning Imager (LI) data in a regional, convection-permitting numerical weather prediction model. (copernicus.org)
Improvements in numerical weather prediction models make it possible to warn of hazardous weather situations. (copernicus.org)

Additionally, by checking the development trajectory of the case company's business and the financial crisis in 2008, the modeling and analysis suggest that the sample company is affected by national macroeconomic factors such as GDP and import & export, and this effect comes with a time lag of one to two years. (hindawi.com)
Covariate adjusted transition intensities are estimated using Cox proportional hazards and Aalen additive hazards models, while the effect of interventions are assessed using methods of inverse probability weighting and G-computation. (biomedcentral.com)

Therefore, google search trends for persimmons could well be modeled by adding a seasonal trend to an increasing growth trend, in what's called a generalized additive model (GAM). (kdnuggets.com)
The cyclic regression model, used to scan state of Iowa information present in the SDRS database for the cyclic pattern of agent detection, was able to characterize a clear seasonal pattern of detection of PDCoV, PEDV, PRRSV, and MHP. (swineweb.com)

This limitation restricts its ability to effectively model complex data distributions and can lead to suboptimal performance in such scenarios. (tutorialspoint.com)

There are conflicting published reports of the relationship between ANGPTL4 function and glucose homeostasis in animal models. (nature.com)
Then, both variables will be estimated together with other explanatory variables such as matrimonial position, sex, instruction degree, experience and age utilizing logistic method to analyze its relationship with early retirement determination. (bluecrewsportsgrill.com)

A systematic approach and a clear model of development are needed to tailor physical activity interventions to the special needs of rural men. (cdc.gov)

Even in low-risk situations, such as when choosing a movie to watch from a streaming platform, a certain measure of trust is required before we surrender hours of our time based on a model. (kdnuggets.com)
2015. Multicriteria and multiobjective models for risk, reliability and maintenance decision analysis. (scielo.br)
In recent years, machine learning models have shown potential to predict the EF risk in IMV patients. (biomedcentral.com)
Overfitting Risk − Another drawback of logistic regression is its susceptibility to overfitting, especially when the number of features exceeds the number of observations in the dataset. (tutorialspoint.com)

or: run two models, one with all the features except the feature of interest (the one you want to assess the performance), and run a second model with all the features, including the feature of interest. (stackexchange.com)

The objective of this study is to model the start-up and growth of a newly established truck transportation company during the economic recession whose main business is seaport containers and bulk inland transportation. (hindawi.com)

This paper presents a modeling method for analyzing a small transportation company's start-up and growth during a global economic crisis which had an impact on China which is designed to help the owners make better investment and operating decisions with limited data. (hindawi.com)
This work has helped to highlight the usefulness of developing a pilot model and shows how the economic model can be further refined in the light of new external data sources. (exeter.ac.uk)
Overfitting occurs when the model becomes overly complex and captures noise or irrelevant patterns, resulting in poor generalization to new data. (tutorialspoint.com)
Sensitivity to Outliers − Logistic regression can be sensitive to outliers, which are data points that deviate significantly from the overall pattern of the dataset. (tutorialspoint.com)
Our LDA can promote missing convection and suppress spurious convection in the initial state of the model, and it has similar skill to the operational radar data assimilation for rainfall forecasts. (copernicus.org)
Toxicological data or PBPK models were not available for the complete mixture of concern. (cdc.gov)
Toxicological data or PBPK models were not available for any of the three- or four-component submixtures. (cdc.gov)

Simplicity − Logistic regression is easy to comprehend and put into practice, which makes it a fantastic option for individuals who are new to the field. (tutorialspoint.com)

The study investigates options to support the reverse logistics for wholesalers in a company. (scielo.br)
For the study in question, two different methodologies have been applied to support the reverse logistics for wholesalers in a company. (scielo.br)
The findings support the importance of integrated care models and mind-body approaches to treating physical and mental health problems simultaneously. (cdc.gov)

A stepwise logistic regression model was used to select key features for developing light-version RNN models. (biomedcentral.com)
The light-version RNN models based on the 26 features selected out of a total of 89 features showed comparable performance as their corresponding full-version models. (biomedcentral.com)
Linearity Assumption − Logistic regression relies on the assumption of a direct connection between features and the logarithm of the target variable's odds. (tutorialspoint.com)

Multi-state modelling, as an extension of traditional survival analysis, offers a unified approach to the modelling of the transitions between such states. (biomedcentral.com)

Learn how to validate a time series model. (kdnuggets.com)

For each taxon and city, the model was built using a random forest method. (springer.com)
Also, the FITradeoff method has been used to identify the alternatives that should compose the portfolio of options concerning the reverse logistics. (scielo.br)
The 1D + 3DVar assimilation method has been adapted to assimilate the W-band reflectivity in the Météo-France kilometre-scale NWP model AROME. (copernicus.org)

SHAP is a game theoretic approach to explain the output of any machine learning model. (kdnuggets.com)

XAI is used to describe an AI model, its expected impact, and potential biases. (kdnuggets.com)
The tool will need fine-tuning before it can be implemented - it would benefit from a user-friendly interface, for one thing - but it highlights the potential that operational models have for helping the military achieve its objectives both in and out of wartime," says Joseph Myers, mathematical sciences division chief at the Army Research Office, an element of U.S. Army Combat Capabilities Development Command's Army Research Laboratory. (ncsu.edu)

In [ 7 ], it is believed that the combination of neural networks and traditional time series analysis is good for forecasting short-term logistic demand for an LTL carrier. (hindawi.com)
Long short-term memory (LSTM) networks are a type of neural networks that builds models based on temporal dependence. (kdnuggets.com)

Diseases5

Chemicals and Drugs2

Analytical, Diagnostic and Therapeutic Techniques and Equipment47

Psychiatry and Psychology3

Phenomena and Processes23

Disciplines and Occupations2

Anthropology, Education, Sociology and Social Phenomena4

Technology, Industry, Agriculture2

Information Science9

Named Groups5

Health Care51

Geographicals6

Center for Additive Manufacturing and Logistics1

Investigated using logistic regr1

Less-than-additive2

Multivariate4

Statistical3

Multiplicative4

Interactions4

AdaBoost1

Manufacturing3

Shapley6

Variants1

Coefficients3

Algorithm1

Analyses1

Transformation1

Framework4

Binary5

Predictions3

Predictive1

AIMS1

Weights2

Mathematical model2

Significance1

Results6

Gradient4

Linear11

Likelihood1

Parameters1

Forecast1

Interaction1

Efficiency1

Functions2

Boosting3

Predictors2

Evaluate4

Outcome3

20222

Prediction4

Effect2

Seasonal2

Scenarios1

Relationship2

Interventions1

Risk4

Assess1

Objective1

Data7

Practice1

Support3

Features3

Survival1

Time series model1

Method3

Approach1

Potential2

Neural2