Search Results for "discriminant analysis"
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Showing 8 open source projects for "discriminant analysis"
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Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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AtteStat
The package for statistical data analysis and applied mathematics
Less means - more power. The high performance open source package for statistical data analysis and applied mathematics AtteStat is an add-in for desktop versions of the Microsoft Excel spreadsheets. Both 32-bit and 64-bit in one package. The combination of the unsurpassed convenience of spreadsheets and the effective interception of Microsoft Excel exceptions (frontend) and the maximum speed of the C++ programming language (backend). Winner of contest Microsoft Office Extensions (PC... -
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Vascular prediction
Study develops predictive model to reduce 90-day readmissions.
...A study developed a predictive model for 90-day hospital readmission in patients undergoing elective vascular procedures. The best predictive model was Shrinkage Discriminant Analysis, which considered variables such as length of stay, comorbidity scores, procedure type, and admission type. The model indicates that efforts to reduce vascular readmissions should prioritize emergency procedures. This risk stratification allows for better identification and prevention of unnecessary readmissions, crucial in an environment where preventing unplanned readmissions is increasingly important. -
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Fuzzy Ecospace Modelling
FEM allows users to create fuzzy functional groups for use in ecology.
...FEM clusters n-dimensional matrices of functional traits (ecospace matrices – here called the Training Matrix) into functional groups and converts them into fuzzy functional groups using fuzzy discriminant analysis (Lin and Chen 2004 – see main text for more information). Following this, FEM classifies the functional entities from a second matrix (the Test Matrix) into the groups made using the Training Matrix, generating fuzzy membership values for each unit in the Test Matrix. These values are real numbers from 0 to 1, representing increasing degrees of “truth” regarding an organism’s membership in the fuzzy set (see main text). ... -
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RDA Toolbox
MATLAB tool for analysis of Raman spectra.
Provides principal component analysis, discriminant analysis, peak analysis, and clustering tools powered by MATLAB in an easy-to-use interface for the interpretation of Raman spectroscopy data. -
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popanc
estimate population ancestry frequencies in admixed populations
This program uses discriminant analysis and Markov chain Monte Carlo to infer local ancestry frequencies in an admixed population from genomic data. This is done in the context of a continuous correlated beta process model that accounts for expected autocorrelations in local ancestry frequencies along chromosomes. This method is best-suited for the analysis of admixed populations that experience little or no on-going gene flow from the parental populations, but that are still segregating for ancestry segments. -
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Online Signature Verification
Real time signature verification using MATLAB and C#
...The signature is characterized as pen-strokes consisting x-y coordinates and pressure with the data being stored in a signature database. Dynamic time warping (DTW) and quadratic discriminant analysis (QDA) is used to get results where the system accepts 2% of forged signatures and rejects 5% of true signatures -
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dAnalytics
dAnalytics is a software made for education in discriminant analysis.
dAnalytics is a software made for educational purposes to work with discriminant analysis. It's a very simple calculator over bi-dimensional populations. You input a file with two columns (one for each variable) and tryout different separations of populations (blue and red) and analyze it's efficiency by observing the eigen value result for the attempted separation. It also gives many information about the statistics both of the input and the separated populations. ... -
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AGNES Cluster identification
R script to run several clustering algorithms using morphometric data
The R script was written to perform and compare several versions of cluster algorithms as described in: Seifert, Ritz & Csősz (2013) published in Myrmecological News. The aim is to identify (cryptic) taxa based on numeric data on morphology. The first step is a Linear Discriminant Analysis (LDA) based on subunits (ant nests) independent of any taxon information. Following analysis are Non-Metric Multidimensional Scaling (NMDS) and k-Means clustering. The NMDS scores are also summarized using K-Means. For comparison, k-Means is also run on the nest means (without preceeding LDA). Cluster assignment is summarized in an output file for all three methods.
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