Analysis

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Related to Discriminant analysis: factor analysis, Cluster analysis

Analysis

The practice of examining information to determine what conclusions it indicates,. The information observed in analysis depends on the type of analysis being conducted. For example, technical analysis uses statistics to determine future price movements of securities, while fundamental analysis looks at indicators of a company's intrinsic value. Analysis may involve qualitative or quantitative information, or both. Most forms of analysis have both strengths and weaknesses.
References in periodicals archive ?
This latter is made up of two main phases: Feature extraction and recognition using a novel Incremental Kernel Nonparametric Discriminant Analysis (IKNDA).
Wang, "Sparse linear discriminant analysis by thresholding for high dimensional data," The Annals of Statistics, vol.
Next, we analyzed the data using discriminant analysis to investigate whether there is any factor(s) specifically significant for low income or high income investors.
Evaluation of sexual size dimorphism in Mangalarga Marchador horses using discriminant analysis. Livest.
The data of hydrochemical component were taken as input variables of the Fisher discriminant analysis model to make calculation for the Fisher discriminant analysis.
Subsequently, different techniques like random forest, Generalized Boosted Regression modelling, Linear Discriminant Analysis, Support Vector Machine and stacked model are used to predict the diagnosis of patients with increased accuracy as obtained before the reduction of number of attributes.
Taking note of the existing studies and growing non-performing loans in Indian public sector banks, the purpose of this study is to demonstrate that multivariate discriminant analysis using both financial and non-financial factors can be used successfully in credit-scoring of business loans by Indian banks.
Discriminant analysis can be used in the diagnosis of the condition of the respiratory system of a person based on the analysis of the composition of EAC using the method of laser correlation spectroscopy.
A discriminant analysis was performed using R code "candis" (30) and "geneig" (31) to identify game-related statistics which discriminate between winning and losing teams in each game type.
Based on the literature survey, Discriminant Analysis and Support Vector Machines were identified as two of the most popular techniques adopted by researchers.
(iii) Extensive experiments on real-world datasets show that our proposed LRKNN regularized graph can significantly boost the performance of Semisupervised Discriminant Analysis.