25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

1. Health care is a human right. 2. The care of the individual is at the center of health care, but the whole system needs to work to improve the health of populations. 3. The health care system must treat illness, alleviate suffering and disability, and promote health. 4. Cooperation with each other, those served, and those in other sectors is essential for all who work in health care. 5. All who provide health care must work to improve it. 6. Do no harm.

https://www.journalacs.org/article/S1072-7515(00)00768-7/pdf

Is this a practical approach

Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato.

Most existing classification approaches assume the underlying training set is evenly distributed. In class imbalanced classification, the training set for one class (majority) far surpassed the training set of the other class (minority), in which, the minority class is often the more interesting class. In this paper, we review the issues that come with learning from imbalanced class data sets and various problems in class imbalance classification. A survey on existing approaches for handling classification with imbalanced datasets is also presented. Finally, we discuss current trends and advancements which potentially could shape the future direction in class imbalance learning and classification. We also found out that the advancement of machine learning techniques would mostly benefit the big data computing in addressing the class imbalance problem which is inevitably presented in many real world applications especially in medicine and social media.

http://home.ijasca.com/data/documents/13IJASCA-070301_Pg176-204_Classification-with-class-imbalance-problem_A-Review.pdf

Classification with class imbalance problem: A review

https://sci2s.ugr.es/keel/workshops/docs/workshop1/2008-FSS-Fernandez-FRBCS_for_imbalanced_ds.pdf

A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

This paper introduces a new technique for feature selection and illustrates it on a real data set Namely, the proposed approach creates subsets of attributes based on two criteria: (1) individual attributes have high discrimination (classification) power; and (2) the attributes in the subset are complementary that is, they misclassify different classes The method uses information from a confusion matrix and evaluates one attribute at a time

/pdf/confusion-matrix-based-feature-selection-q3vij9j3d8.pdf

Confusion Matrix-Based Feature Selection

The process of plant domestication is often protracted, involving underexplored intermediate stages with important implications for the evolutionary trajectories of domestication traits. Previously, tomato domestication history has been thought to involve two major transitions: one from wild Solanum pimpinellifolium L. to a semidomesticated intermediate, S. lycopersicum L. var. cerasiforme (SLC) in South America, and a second transition from SLC to fully domesticated S. lycopersicum L. var. lycopersicum in Mesoamerica. In this study, we employ population genomic methods to reconstruct tomato domestication history, focusing on the evolutionary changes occurring in the intermediate stages. Our results suggest that the origin of SLC may predate domestication, and that many traits considered typical of cultivated tomatoes arose in South American SLC, but were lost or diminished once these partially domesticated forms spread northward. These traits were then likely reselected in a convergent fashion in the common cultivated tomato, prior to its expansion around the world. Based on these findings, we reveal complexities in the intermediate stage of tomato domestication and provide insight on trajectories of genes and phenotypes involved in tomato domestication syndrome. Our results also allow us to identify underexplored germplasm that harbors useful alleles for crop improvement.

/pdf/genomic-evidence-for-complex-domestication-history-of-the-qc8tpqiacz.pdf

Genomic Evidence for Complex Domestication History of the Cultivated Tomato in Latin America.

The control of tomato fruit elongation orchestrated by sun, ovate and fs8.1 in a wild relative of tomato.

This study evaluates the robustness of a fuzzy classifier when class distribution of the training set varies. The analysis of the results is based on the classification accuracy and ROC curves. The experimental results reported here show that fuzzy classifiers are less variant with the class distribution and less sensitive to the imbalance factor than decision trees

/pdf/the-effect-of-imbalanced-data-class-distribution-on-fuzzy-2lg0r1qraz.pdf

The Effect of Imbalanced Data Class Distribution on Fuzzy Classifiers - Experimental Study

Classification and characterization of the shape of plant organs are important tools for plant biologists, breeders and growers. Here we use boundary measurements, i.e. contour morphometric data, of scanned tomato fruits in conjunction with elliptic Fourier shape modeling and Bayesian classification techniques to find the optimum number of shape categories. Our findings show that there are nine computationally and visually distinct tomato shape categories: ellipsoid, flat, heart, long, long rectangular, rectangular, round, obovoid, and oxheart. Analyses of fruits from a diverse set of tomato accessions demonstrate that some varieties carry fruits that conform to predominantly one shape category while others carry fruits that conform to multiple shape categories. In particular the categories oxheart and long rectangular feature fruit that tend to equivalently fit several categories of shape, while the flat and obovoid categories contain fruit that consistently conform exclusively to a single category. The findings show that elliptic Fourier shape modeling and Bayesian classification provide an excellent tool for further in depth analyses of fruit shape variation that may occur across varieties and/or result from growth under different environmental conditions.

Sofia Visa

Papers

Confusion Matrix-Based Feature Selection

Genomic Evidence for Complex Domestication History of the Cultivated Tomato in Latin America.

The control of tomato fruit elongation orchestrated by sun, ovate and fs8.1 in a wild relative of tomato.

The Effect of Imbalanced Data Class Distribution on Fuzzy Classifiers - Experimental Study

Modeling of tomato fruits into nine shape categories using elliptic fourier shape modeling and Bayesian classification of contour morphometric data