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Discriminant Analysis

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Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.

Journal of neuroscience methods
BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized ...

A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and -Nearest Neighbor Graph.

Computational intelligence and neuroscience
Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, ...

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

Journal of neural engineering
OBJECTIVE: Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a...

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.

The Science of the total environment
Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein ...

Robust differential expression analysis by learning discriminant boundary in multi-dimensional space of statistical attributes.

BMC bioinformatics
BACKGROUND: Performing statistical tests is an important step in analyzing genome-wide datasets for detecting genomic features differentially expressed between conditions. Each type of statistical test has its own advantages in characterizing certain...

Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees.

Neural networks : the official journal of the International Neural Network Society
The success of myoelectric pattern recognition (M-PR) mostly relies on the features extracted and classifier employed. This paper proposes and evaluates a fast classifier, extreme learning machine (ELM), to classify individual and combined finger mov...

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

Neural networks : the official journal of the International Neural Network Society
Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels...

Combining machine learning and matching techniques to improve causal inference in program evaluation.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balan...

Predictive models reduce talent development costs in female gymnastics.

Journal of sports sciences
This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection proced...

Using machine learning to model dose-response relationships.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Establishing the relationship between various doses of an exposure and a response variable is integral to many studies in health care. Linear parametric models, widely used for estimating dose-response relationships, h...