Search results for "Quadratic classifier"

Multi-Temporal Image Classification with Kernels

2009

Breaking the curse of dimensionality in quadratic discriminant analysis models with a novel variant of a Bayes classifier enhances automated taxa ide…

2013

Macroinvertebrate samples are commonly used in biomonitoring to study changes on aquatic ecosystems. Traditionally, specimens are identified manually to taxa by human experts being time-consuming and cost intensive. Using the image data of 35 taxa and 64 features, we propose a novel variant of the quadratic discriminant analysis for breaking the curse of dimensionality in quadratic discriminant analysis models. Our variant, called a random Bayes array (RBA), uses bagging and random feature selection similar to random forest. We explore several variations of RBA. We consider three classification (i.e taxa identification) decisions: majority vote, averaged posterior probabilities, and a novel…

SIMULATION EXPERIMENTS WITH MULTIPLE GROUP LINEAR AND QUADRATIC DISCRIMINANT ANALYSIS

1973

Summary A simulation program is described which can be performed to obtain estimates of the different types of misclassification probabilities for multiple group linear and quadratic discriminant analysis. The program can be used to study how these errors depend on sample sizes and the different parameters of the multivariate normal distribution. Examples for several simulation experiments are given and possible conclusions are discussed.

QSAR models for tyrosinase inhibitory activity description applying modern statistical classification techniques: A comparative study

2010

Abstract Cluster analysis (CA), Linear and Quadratic Discriminant Analysis (L(Q)DA), Binary Logistic Regression (BLR) and Classification Tree (CT) are applied on two datasets for description of tyrosinase inhibitory activity from molecular structures. The first set included 701 tyrosinase inhibitors (TI) that are used for performance of inhibitory and non-inhibitory activity and the second one is for potency estimation of active compounds. 2D TOMOCOMD-CARDD atom-based quadratic indices are computed as molecular descriptors. CA is used to “rational” design of training (TS) and prediction set (PS) but it shows of not being adequate as classification technique. On the first data, the overall a…

<title>Expanding context against weighted voting of classifiers</title>

2000

In the paper we propose a new method to integrate the predictions of multiple classifiers for Data Mining and Machine Learning tasks. The method assumes that each classifier stands in it's own context, and the contexts are partially ordered. The order is defined by monotonous quality function that maps each context to the value from the interval [0,1]. The classifier that has the context with better quality is supposed to predict better than the classifier from worse quality. The objective is to generate the opinion of `virtual' classifier that stands in the context with quality equal to 1. This virtual classifier must have the best accuracy of predictions due to the best context. To do thi…

Quality based classification of gasoline samples by ATR-FTIR spectrometry using spectral feature selection with quadratic discriminant analysis

2013

Abstract A chemometric approach has been developed for characterization of gasoline samples regarding their quality. Attenuated total reflectance – infrared spectrometric data were processed by genetic algorithm (GA) and successive projection algorithm (SPA) feature selection techniques, being employed as an initial step prior to apply a discriminative tool. It was aimed to classify the fuel samples according to their quality passed/failed data. Chemometric predictive procedures were developed using quadratic discriminant analysis (QDA) combined with GA and SPA as a feature subset and feature selection strategy. Results showed 93.3% and 95.6% accuracy for SPA-QDA and GA-QDA models respectiv…

Parasite infracommunities as predictors of harvest location of bogue (Boops boops L.): a pilot study using statistical classifiers

2005

The accuracy of classifying bogue (Boops boops) according to the fishery from which it was harvested was evaluated by applying several statistical classification techniques to fish parasite abundances. Bogue captured in 2001 in two fisheries off the Atlantic coast of Spain were compared with one off the Spanish Mediterranean coast. One hundred bogue were classified to each harvest location (fishery) using different numbers of parasite species chosen as predictors by a best subset method. Two parametric methods of classification (linear and quadratic discriminant analysis) were compared with two non-parametric approaches (k-nearest neighbour classification and feed-forward neural network) an…

A genetic integrated fuzzy classifier

2005

This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.

On the Construction of Optimum Categories in Biomedical Data Recognition Problems

1979

The recognition of patterns within sets of biomedical data involves the following problems: a) Proper recording of the data to be used b) Extraction of suitable features c) Choice of categories or classes which are relevant to the medical decision task d) Estimation of the underlying distributions in the case of using parametric methods e) Choice of an adequate classification rule Whereas a lot of theories and procedures exists for most of these steps — particularly in the field of computer-aided differential diagnosis of electrocardiograms (ECG) (see [6]) — there has been only rare considerations on the problems of definition of appropriate categories.

Assessment of haemophilic arthropathy through balance analysis: a promising tool

2019

[EN] The purpose of this study was to develop a tool able to distinguish between subjects who have haemophilic arthropathy in lower limbs and those who do not by analyzing the centre of pressure displacement. The second objective was to assess the possible different responses of haemophiliacs and healthy subjects by creating a classifier that could distinguish between both groups. Fiftyfour haemophilic patients (28 with and 26 without arthropathy) and 23 healthy subjects took part voluntarily in the study. A force plate was used to measure postural stability. A total of 276 centre of pressure displacement parameters were calculated under different conditions: unipedal/bipedal balance with e…