Cluster validity

Ebook "Chemometrics with R: Multivariate data analysis in the natural sciences and life sciences" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a comprehensive description of the general data analysis paradigm, from exploratory analysis (principal component analysis, self-organizing maps and clustering) to modeling (classification, regression) and validation (including variable selection).

289p tachieuhoa 28-01-2024 4 2   Download

The association between autophagy and immunity, including infiltrating immunocytes, immune reaction gene-sets, and HLAs (human leukocyte antigen) gene, remains unclear. The present study aimed to provide a valid diagnostic tool for coronary artery disease (CAD), and explore the pathological mechanisms of CAD based on the association between autophagy and immunity.

14p vihagrid 30-01-2023 6 3   Download

Lecture Data mining: Lesson 14. The main topics covered in this chapter include: cluster analysis; model-based clustering methods; model based clustering; assuming d-dim Gaussian distributions; cluster validity; measures of cluster validity;... Please refer to the content of document.

26p tieuvulinhhoa 22-09-2022 7 4   Download

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters.

12p vilarryellison 29-10-2021 13 1   Download

Carex L. is one of the largest genera in the Cyperaceae family and an important vascular plant in the ecosystem. However, the genetic background of Carex is complex and the classification is not clear. In order to investigate the gene function annotation of Carex, RNA-sequencing analysis was performed.

15p vijichea2711 28-05-2021 12 1   Download

The treat-to-target (T2T) approach to the care of patients with rheumatoid arthritis involves using validated metrics to measure disease activity, frequent follow-up visits for patients with moderate to high disease activity, and escalation of therapy when patients have inadequate therapeutic response as assessed by standard disease activity scores.

7p viannito2711 20-04-2021 14 2   Download

Fibromyalgia (FM) is a pain syndrome, the mechanisms and predictors of which are still unclear. We have earlier validated a set of FM-symptom questions for detecting possible FM in an epidemiological survey and thereby identified a cluster with “possible FM”. This study explores prospectively predictors for membership of that FM-symptom cluster.

11p vioregon2711 22-02-2021 12 2   Download

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization.

11p viwyoming2711 16-12-2020 8 0   Download

The ability to understand another’s emotions and act appropriately, empathy, is an important mediator of relationship function and health intervention fidelity. We adapted the Interpersonal Reactivity Index (IRI) – an empathy scale – among seroconcordant expectant couples with HIV in the Homens para Saúde Mais (HoPS+) trial – a cluster randomized controlled trial assessing couple-based versus individual treatment on viral suppression – in Zambézia Province, Mozambique.

12p vigeorgia2711 30-11-2020 11 1   Download

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved.

10p vikentucky2711 26-11-2020 14 0   Download

Workflows, or computational pipelines, consisting of collections of multiple linked tasks are becoming more and more popular in many scientific fields, including computational biology. For example, simulation studies, which are now a must for statistical validation of new bioinformatics methods and software, are frequently carried out using the available workflow platforms.

19p vikentucky2711 24-11-2020 14 1   Download

Presence of circulating tumor cells (CTCs) is a validated prognostic marker in metastatic breast cancer. Additional prognostic information may be obtained by morphologic characterization of CTCs.

15p vinaypyidaw2711 26-08-2020 9 2   Download

In the present work, attempts have been made to analyze the Iris data set with clustering technique which is the main task of exploratory data mining and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval and bioinformatics. The Iris flower data set is a popular multivariate data set introduced by Sir Ronald Fisher as an example of discriminant analysis.

10p angicungduoc6 22-07-2020 17 3   Download

Milk protein fibre is made out of skimmed milk. Main components of this fibre are casein proteins, drawn from the cow’s milk. It is responsible for the white, opaque appearance of milk in which it is combined with calcium and phosphorus as clusters of casein molecules, called micelles. This fiber contains eighteen types of amino-acids extracts that helps in the nourishments of the skin and makes it healthier. Milk protein fibre is a blend of nature, science and technology that has benefits of natural as well as synthetic fibre.

8p nguathienthan4 18-04-2020 22 1   Download

Measuring the quality of a clustering algorithm has shown to be as important as the algorithm itself. It is a crucial part of choosing the clustering algorithm that performs best for an input data. Streaming input data have many features that make them much more challenging than static ones.

13p vithanos2711 09-08-2019 17 1   Download

The prediction model was developed using training data, and validated using independent test data. The data was generated from simulations of the optimized power reactor 1000 (OPR1000) using MAAP4 code. The informative data for training the FNN model was selected using the subtractive clustering method. The prediction performance of the reactor vessel water level was quite satisfactory, but a few large errors were occasionally observed.

8p minhxaminhyeu5 30-06-2019 15 0   Download

In terms of the model configurations, the simulation-based approach used to validate our proposed technique indicates that scenarios where member nodes of a cluster was not needed for computation required for less resources for data transmission with increased energy consumption than scenarios that required both member nodes and cluster heads for computation.

7p blossom162 31-03-2019 25 0   Download

In this paper, the authors introduce a method for evaluating the performance of unsupervised anomaly detection techniques. The method is based on the application of internal validation metrics in clustering algorithms to anomaly detection. The experiments were conducted on a number of benchmarking datasets. The results are compared with the result of a recent proposed approach that shows that some proposed metrics are very consistent when being used to evaluate the performance of unsupervised anomaly detection algorithms.

14p thuyliebe 04-10-2018 24 0   Download

We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achieving 82% accuracy in this task when each conjunction is considered independently. Combining the constraints across many adjectives, a clustering algorithm separates the adjectives into groups of different orientations, and finally, adjectives are labeled positive or negative. ...

8p bunthai_1 06-05-2013 38 5   Download

This paper presents an unsupervised word sense learning algorithm, which induces senses of target word by grouping its occurrences into a “natural” number of clusters based on the similarity of their contexts. For removing noisy words in feature set, feature selection is conducted by optimizing a cluster validation criterion subject to some constraint in an unsupervised manner. Gaussian mixture model and Minimum Description Length criterion are used to estimate cluster structure and cluster number. ...

8p bunbo_1 17-04-2013 45 1   Download