34 The Impact of Truncating Data on the Predictive Ability of Selection Candidate EBV in Swine Using Ssgblup.

2018 ◽  
Vol 96 (suppl_2) ◽  
pp. 18-19
Author(s):  
J T Howard ◽  
T A Rathje ◽  
C E Bruns ◽  
D F Wilson-Wells ◽  
S D Kachman ◽  
...  
Keyword(s):  
Predictive Ability ◽  
Selection Candidate ◽  
The Impact

scholarly journals Applying the Metafounders Approach for Genomic Evaluation in a Multibreed Beef Cattle Population

2020 ◽  
Vol 11 ◽  
Author(s):  
Vinícius Silva Junqueira ◽  
Paulo Sávio Lopes ◽  
Daniela Lourenco ◽  
Fabyano Fonseca e Silva ◽  
Fernando Flores Cardoso
Keyword(s):  
Beef Cattle ◽  
Variance Components ◽  
Genetic Relationships ◽  
A Priori ◽  
Predictive Ability ◽  
Single Step ◽  
Pedigree Information ◽  
Phenotypic Variance ◽  
Genomic Information ◽  
The Impact

Pedigree information is incomplete by nature and commonly not well-established because many of the genetic ties are not known a priori or can be wrong. The genomic era brought new opportunities to assess relationships between individuals. However, when pedigree and genomic information are used simultaneously, which is the case of single-step genomic BLUP (ssGBLUP), defining the genetic base is still a challenge. One alternative to overcome this challenge is to use metafounders, which are pseudo-individuals that describe the genetic relationship between the base population individuals. The purpose of this study was to evaluate the impact of metafounders on the estimation of breeding values for tick resistance under ssGBLUP for a multibreed population composed by Hereford, Braford, and Zebu animals. Three different scenarios were studied: pedigree-based model (BLUP), ssGBLUP, and ssGBLUP with metafounders (ssGBLUPm). In ssGBLUPm, a total of four different metafounders based on breed of origin (i.e., Hereford, Braford, Zebu, and unknown) were included for the animals with missing parents. The relationship coefficient between metafounders was in average 0.54 (ranging from 0.34 to 0.96) suggesting an overlap between ancestor populations. The estimates of metafounder relationships indicate that Hereford and Zebu breeds have a possible common ancestral relationship. Inbreeding coefficients calculated following the metafounder approach had less negative values, suggesting that ancestral populations were large enough and that gametes inherited from the historical population were not identical. Variance components were estimated based on ssGBLUPm, ssGBLUP, and BLUP, but the values from ssGBLUPm were scaled to provide a fair comparison with estimates from the other two models. In general, additive, residual, and phenotypic variance components in the Hereford population were smaller than in Braford across different models. The addition of genomic information increased heritability for Hereford, possibly because of improved genetic relationships. As expected, genomic models had greater predictive ability, with an additional gain for ssGBLUPm over ssGBLUP. The increase in predictive ability was greater for Herefords. Our results show the potential of using metafounders to increase accuracy of GEBV, and therefore, the rate of genetic gain in beef cattle populations with partial levels of missing pedigree information.

scholarly journals Establishment of a Financial Crisis Early Warning System for Domestic Listed Companies Based on Three Decision Tree Models

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Gang Wang ◽  
Keming Wang ◽  
Yingying Zhou ◽  
Xiaoyan Mo ◽  
Weilin Xiao
Keyword(s):  
Financial Crisis ◽  
Decision Tree ◽  
Early Warning ◽  
Financial Management ◽  
Early Warning System ◽  
Comprehensive Evaluation ◽  
Warning System ◽  
Predictive Ability ◽  
Tree Models ◽  
The Impact

The financial crisis is a realistic problem that the general enterprise must encounter in the process of financial management. Due to the impact of the COVID-19 and the Sino-US trade war, domestic companies with unsound financial conditions are at risk of shutdowns and bankruptcies. Therefore, it is urgently needed to study the financial warning of enterprises. In this study, three decision tree models are used to establish the financial crisis early warning system. These three decision tree models include C50, CART, and random forest decision trees. In addition, the ROC curve was used for comprehensive evaluation of the accuracy analysis of the model to confirm the predictive ability of each model. This result can provide reference for domestic financial departments and provide financial management basis for the investing public.

A Note on Psychological Distance and Export Market Selection

2000 ◽  
Vol 8 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Douglas Dow
Keyword(s):  
Geographic Distance ◽  
Predictive Ability ◽  
Psychological Distance ◽  
Export Market ◽  
Market Selection ◽  
Foreign Markets ◽  
Single Item ◽  
Independent Panel ◽  
The Impact ◽  
Early Market

The concept of psychological distance, or psychic distance, was first proposed by Beckerman (1956) and later popularized by Johanson and Vahlne (1977) . However, efforts to test the impact of psychological distance on export market selection have been sporadic and flawed. The author calibrates a single-item indicator of psychological distance using an independent panel of experts. The predictive ability of the resulting instrument is then tested on the order in which Australian exporters select their first five foreign markets. The author then compares this instrument with three other scales that are commonly employed as indicators of psychological distance. Scales based on Sethi's (1971) and Hofstede's (1980) work prove to be inferior predictors of early market selection. Geographic distance is found to be a significant predictor, but its effect is largely independent of psychological distance. The author also explores the dynamic nature of psychological distance. The impact of psychological distance on market selection appears to decrease substantially after the first market entry decision but remains a significant predictor.

scholarly journals Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce 

2020 ◽  
Author(s):  
Linghua Zhou(Former Corresponding Author) ◽  
Zhiqiang Chen ◽  
Lars Olsson ◽  
Thomas Grahn ◽  
Bo Karlsson ◽  
...  
Keyword(s):  
Norway Spruce ◽  
Microfibril Angle ◽  
Predictive Ability ◽  
Tree Breeding ◽  
Wood Properties ◽  
Tree Age ◽  
Breeding Cycle ◽  
Standing Tree ◽  
Increment Core ◽  
The Impact

Abstract BACKGROUND: Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. RESULTS: GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12. CONCLUSIONS: This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

scholarly journals The impact of data-complexity and team characteristics on performance in the classification model

2022 ◽  
Vol 9 (1) ◽  
pp. 0-0
Keyword(s):  
Machine Learning ◽  
Binary Classification ◽  
Class Imbalance ◽  
Predictive Ability ◽  
Predictive Performance ◽  
Classification Model ◽  
Data Complexity ◽  
High Performing ◽  
Machine Learning Model ◽  
The Impact

This article investigates the impact of data-complexity and team-specific characteristics on machine learning competition scores. Data from five real-world binary classification competitions hosted on Kaggle.com were analyzed. The data-complexity characteristics were measured in four aspects including standard measures, sparsity measures, class imbalance measures, and feature-based measures. The results showed that the higher the level of the data-complexity characteristics was, the lower the predictive ability of the machine learning model was as well. Our empirical evidence revealed that the imbalance ratio of the target variable was the most important factor and exhibited a nonlinear relationship with the model’s predictive abilities. The imbalance ratio adversely affected the predictive performance when it reached a certain level. However, mixed results were found for the impact of team-specific characteristics measured by team size, team expertise, and the number of submissions on team performance. For high-performing teams, these factors had no impact on team score.

scholarly journals The impact of truncating data on the predictive ability for single-step genomic best linear unbiased prediction

2018 ◽  
Vol 135 (4) ◽  
pp. 251-262 ◽  
Author(s):  
Jeremy T. Howard ◽  
Tom A. Rathje ◽  
Caitlyn E. Bruns ◽  
Danielle F. Wilson-Wells ◽  
Stephen D. Kachman ◽  
...  
Keyword(s):  
Predictive Ability ◽  
Best Linear Unbiased Prediction ◽  
Single Step ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
The Impact ◽  
Unbiased Prediction

scholarly journals Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury

2022 ◽  
Vol 11 ◽  
Author(s):  
Qing-Hua Du ◽  
Jian Li ◽  
Yi-Xiu Gan ◽  
Hui-Jun Zhu ◽  
Hai-Ying Yue ◽  
...  
Keyword(s):  
Brain Injury ◽  
Dose Distribution ◽  
Predictive Ability ◽  
Volume Effect ◽  
Equivalent Uniform Dose ◽  
Critical Dose ◽  
Dose Volume ◽  
Radiation Induced ◽  
Effect Parameter ◽  
The Impact

PurposeTo study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements.Methods and MaterialsThe brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; VD with different D for different distributions). Predictive ability of EUDVD (EUD of VD) for radiation-induced brain injury was assessed by receiver operating characteristics curve (ROC) and area under the curve (AUC). The optimal volume-effect parameter a of EUD was selected when AUC was maximal (mAUC). Correlations between mAUC, a and D were analyzed by Pearson correlation analysis. Both mAUC and a in brain and half-brain were compared by using paired samples t-tests. The optimal DV and VD points were selected for a simple comparison.ResultsThe mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal a value was 21.5/22. When D increased, mAUC of EUDVD increased, while a decreased. The mAUC reached the maximum value when D was 50–55 Gy, and a was always 1 when D ≥55 Gy. The difference of mAUC/a between brain and half-brain was not significant. If a was in range of 1 to 22, AUC of brain/half-brain EUDV55 Gy (0.857–0.830/0.845–0.830) was always larger than that of brain/half-brain EUD (0.681–0.819/0.691–0.821). The AUCs of optimal dose/volume points were 0.801 (brain D2.5 cc), 0.823 (brain V70 Gy), 0.818 (half-brain D1 cc), and 0.827 (half-brain V69 Gy), respectively. Mean dose (equal to EUDVD with a = 1) of high-dose volume (V50 Gy–V60 Gy) was superior to traditional EUD and dose/volume points.ConclusionVolume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability.

A Simple One-Dimensional Model for Primary Turbine Blade Erosion Prediction

1983 ◽  
Author(s):  
J. L. Dussourd
Keyword(s):  
Turbine Blades ◽  
Predictive Ability ◽  
Bluff Bodies ◽  
One Dimensional ◽  
Erosion Prediction ◽  
Blade Cascade ◽  
Blade Row ◽  
Quantitative Manner ◽  
First Order Method ◽  
The Impact

Sophisticated models to predict the erosion process in turbine blades exposed to dust laden gas stream quickly become complex and tedious for use for everyday engineering applications. A simpler model for primary erosion can be formulated by assimilating the blade row to a device having a certain size and deflecting the stream through a given angle and at a given rate. The technology which exists for particle impacts physics with bluff bodies can be adapted to cascades. Thus, basically the model is derived from first principles. This approach is formulated in a quantitative manner in terms of cascade parameters, gas properties, and particulate parameters. The result is a simple equation which is easy to use and the physics of which are logical and intuitively reasonable. Its predictive ability, however, is limited to the frequency of impacts and the strength of the impacts. It does not address the mechanics of the impact process or the properties of the material being impacted. These variables are introduced through an experimental coefficient which, as it turns out, is the only experimental input in the analysis. The method is tested against quite a few experimental cases with a degree of predictive ability which is acceptable in a simple, first order method. The agreement is thought to be at least as good as the credibility or accuracy of the test data. The method is finally applied to study the effects of various blade cascade parameters on erosion resistance, the results of which are presented in the form of general curves.

Age-adjusted infarct volume cut-off points improve stroke outcome prognostication beyond modeling with age and infarct volume

2021 ◽  
pp. neurintsurg-2020-017066
Author(s):  
Mehdi Bouslama ◽  
Diogo C Haussen ◽  
Gabriel Martins Rodrigues ◽  
Clara M Barreira ◽  
Seena Dehkharghani ◽  
...  
Keyword(s):  
Infarct Volume ◽  
Care Center ◽  
Tertiary Care ◽  
Age Groups ◽  
Predictive Ability ◽  
Youden Index ◽  
Anterior Circulation ◽  
Vessel Occlusion ◽  
Good Outcome ◽  
The Impact

BackgroundAge and infarct volume are among the most powerful predictors of outcome after large vessel occlusion acute strokes (LVOS).ObjectiveTo study the impact of age-adjusted final infarct volume (FIV) on functional outcomes.MethodsReview of a prospectively collected thrombectomy database at a tertiary care center between September 2010 and February 2018. Consecutive patients with anterior circulation LVOS who achieved full reperfusion (modified Thrombolysis in Cerebral Infarction 3) were categorized into four age groups: (G1) <60 years, (G2) 60–69, (G3) 70–79, (G4) ≥80 years. The Youden Index was used to identify the optimal FIV cut-off point for good outcome (modified Rankin Scale score 0–2) discrimination in each group and the overall population. The predictive ability of these specific thresholds was evaluated using binary logistic regressions and compared with the non-age-adjusted cut-off point.Results516 patients were analyzed (G1: n=171, G2: n=130, G3: n=103, G4: n=112). Patients with poor outcome had a larger FIV in each group (p<0.01 for all). The target FIV cut-off point decreased with increased age: G1: 45.7 mL (sensitivity 56%, specificity 80%); G2: 30.4 mL (sensitivity 63%, specificity 75%); G3: 20.2 mL (sensitivity 76%, specificity 65%); G4: 16.9 mL (sensitivity 68%, specificity 70%). The non-age-adjusted cut-off point was 19.2 mL (sensitivity 70%, specificity 59%).In multivariate analysis, adjusting for confounders including age and FIV, achieving a FIV less than the age-adjusted threshold was an independent predictor of good outcome (aOR=2.72, 95% CI 1.41 to 5.24, p<0.001). In contrast, a similar model including the non-age-adjusted target cut-off point failed to reveal an association with good outcome (aOR=1.72, 95% CI 0.93 to 3.19, p<0.085). Furthermore, the latter model had a weaker outcome predictive ability as assessed by the Akaike information criterion (409 vs 403).ConclusionsAge-adjusted infarct volume represents a strong outcome discriminator beyond age and infarct volume in isolation and might help to refine patient selection and improve outcome prognostication in stroke thrombectomy.

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