Step-Wise Regression
Statistical Models for Long range Forecasting of Southwest Monsoon Rainfall over India Using Step Wise Regression and Neural Network
... power regression models used from 2003 to 2006 and new statistical ensemble forecasting system are ...linear regression and neural network techniques based upon training set of the 43 years of data from ...
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Effects of the Pursuit herbicide on relationships of morphological and physiological traits of two species of Trifolium pretense L. and Trifolium alexandrinum L.
... of step-wise regression analysis are presented in Table ...significant regression relationship between remaining traits of model and biomass ...of step-wise regression ...
6
Sound Around Town: Sense of Place and the Perception of the Acoustic Environment.
... The variables that went into the step wise regression include: sense of place constructs for sociocultural place meaning, environmental place meaning, nature relatedness: outdoors/c[r] ...
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Comparison of feature selection method for chronic kidney data set using data mining classification analytical model
... of Step wise Regression Classification (SRC) Model and Built around the Random Forest Classification algorithm (BRFC) feature selection, subset (data) of Kidney dataset from whole normalized Kidney ...
13
Variation among Beef Bulls in the Ratio of X to Y Chromosome Bearing Spermatozoa
... Within bulls, step-wise regression was used to determine correlations between sperm parameters measured by CASA or sperm morphology, and the ratio of X-chromosome bearing sperm in semen [r] ...
8
A study of non-response
... non-response, REFUSAL, LEFT CANBERRA and NOT AVAILABLE, were determined for each type by applying the step-wise regression described in Section 4.4 to an initial set which consisted of t[r] ...
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Yellow flag scores in a compensable New Zealand cohort suffering acute low back pain
... each step (LRs ...the step wise regression models, there were signifi cant and elevated probabilities that moderate, and at-risk yellow fl ag classifi cations would predict claims lasting longer ...
12
Vol 5, No 12 (2017)
... significant regression expression. For achieving this goal we have carried out step-wise regression analysis following the multiple linear regression ...in step wise ...
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Probing depth is an independent risk factor for HbA1c levels in diabetic patients under physical training: a cross-sectional pilot-study
... training; step- wise regression analysis showed that fasting glucose levels, cardiorespiratory fitness, diastolic blood pres- sure, probing depth and BMI are risk factors for high concentrations of ...
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Comparison of Feature Selection Methods for Chronic Kidney Data Set using Data Mining Classification Analytical Model
... of Step wise Regression Classification (SRC) Model and Built around the Random Forest Classification algorithm (BRFC) feature selection, subset (data) of Kidney dataset from whole normalized Kidney ...
11
Geospatial examination of lithium in drinking water and suicide mortality
... stepwise regression model reveals that they are normally distribu- ted (Jarque Bera test (JB) = ...final step- wise regression model is statistically highly ...
8
Maintainability Model with Object-Oriented Software Metrics
... models with the help of regression approach. In these models several independent factors were taken into account of the maintainability model. This model took much time to calculate the maintainability model and ...
7
<p>A New Method for Prediction of Dental Arch Perimeter</p>
... Materials and methods: Sixty-seven pairs of study models for patients with normal occlusion who received dental treatment were included in this study. Dental arch width at the level of the canines, fi rst premolars, and fi ...
5
Study the Dynamics and Variability of River Indus Flow
... Step-wise regression is an iterative method and an automated tool used in the exploratory stages of building linear regression model from a subset of different independent ...each step. ...
10
On $b$-bit Min-wise Hashing for Large-scale Regression and Classification with Sparse Data
... Approximating kernel methods using random feature expansions was pioneered by Rahimi and Recht (2007) who used random Fourier features to approximate translation invariant kernels such as the Gaussian kernel. Sutherland ...
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Multi Step Regression Learning for Compositional Distributional Semantics
... It leaves open the question of how to learn tensors of specific ranks. This, very much like in the case of the DisCoCat framework of Coecke et al. (2010) from which it originated, is intentional: There may be more than ...
11
MCDM Approach for the Adoption of Best Cloud
... The basic structure of ANP is a network having clusters and connecting nodes. A pair wise comparison and judgment are made to make a decision. The processing is developed between the elements and analysis is done ...
7
The rate of blastocysts production following vitrification with step-wise equilibration of immature mouse oocytes
... Materials and Methods: Oocytes were obtained from 4 weeks old female mice 48h after intraperitoneal injection of 7.5 IU pregnant mare serum gonadotropin (PMSG). Collected oocytes before vitrification were exposed to ...
6
VARIETAL DEVELOPMENT PROGRAM AT SUGARCANE RESEARCH INSTITUTE, FAISALABAD
... Plantation at this stage is made in plots 32 m 2 with 5 repeats using RCBD in spring.(three repeats for data collection and 2 for periodic juice analysis ). Data on same aspects are collected while for quality ...
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Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models
... nonparametric regression model (14) sequentially. In each step of Algorithm 1, we select the tuning parameter using a five-fold cross-validation on the training data ...linear regression with two-way ...
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