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PubMed2006

[Spectra classification based on generalized discriminant analysis].

A kernel based generalized discriminant analysis (GDA) technique is proposed for the classification of stars, galaxies, and quasars. GDA combines the LDA algorithm with kernel trick, and samples are projected by nonlinear mapping onto the feature space F with high dimensions, and then LDA is conducted in F. Also, it could be inferred that GDA which combines the extension of Fisher's criterion with kernel trick is complementary to kernel Fisher discriminant framework. LDA, GDA, PCA and KPCA were experimentally compared with these three different kinds of spectra. Among these four techniques, GDA obtains the best result, followed by LDA, and PCA is the worst. Although KPCA is also a kernel based technique, its performance is not satisfactory if the selected number of the principal components is small, and in some cases, it appears even worse than LDA, a non-kernel based technique.

English Abstract↗
PubMed1997

[Multivariate discriminant analysis for assessing mental workload during duel task operation].

In order to investigate the efficiency of multivariate discriminant analysis in the assessment of mental workload during dual task operations, various psychophysiological indices and performance were recorded. The dual task consisted of the primary visual tracking task and the secondary Oddball task. The results indicated that tracking error, latency of P3 and IBI of HR correlated well with the mental workload and the multivariate discriminant analysis succeeded in classifying the levels of mental workload with higher conformation rate than those using the single index. It suggests that multivariate discriminant analysis is meaningful in the assessment of mental workload under dual task situations.

Aerospace Medicine↗
PubMed1991

Discriminant analysis of iron deficiency anaemia and heterozygous thalassaemia traits: a 3-dimensional selection of red cell indices.

The two main causes of microcytic and hypochromic anaemia are iron deficiency and thalassaemia traits. Discriminant analysis based on a simple combination of classical red cell indices have been used to differentiate between iron deficiency anaemia and thalassaemia with varying degree of accuracy. Two new indices are now available from modern cell counters: red cell distribution width (RDW) and haemoglobin concentration distribution (HDW). Our discriminant analysis suggests that RBC, MCHC and RDW contribute significantly to the differentiation between iron deficiency anaemia and thalassaemia in both healthy donors and hospital-patient groups. In the discriminating process, previous workers have overlooked the heterogeneity of anaemia between anaemic groups as well as biological differences in MCV and MCH among the alpha and beta thalassaemia subjects. This study took into account of these biases and proved, for the first time, that differentiation between iron deficiency and thalassaemia by discriminant analysis was clinically reliable and not significantly biased by the severity of anaemia. The diagnostic accuracy of discriminant analysis was confirmed retrospectively by the reallocation algorithm using the jack-knife principle and prospectively by testing the discriminant functions on independent new samples. Selection of the red cell indices contributing to the discrimination of microcytic hypochromic anaemia was based on biological and statistical considerations. The clear separation of red cell index data of iron deficiency anaemia and thalassaemia traits was shown 3-dimensionally by surface plots.

Anemia, Hypochromic↗
PubMedDate not supplied

Risk factors for peripheral atherosclerosis. Retrospective evaluation by stepwise discriminant analysis.

To evaluate the optimal discriminators for peripheral atherosclerosis, we studied retrospectively 49 male patients and 39 male controls between 40 and 60 years of age. In addition to hypertension, cigarette smoking, diabetes mellitus, and hyperuricemia, we determined the most common lipids, lipoproteins, and apolipoproteins. Highly significant differences of median values between patients and controls in decreasing order of magnitude were recorded for apo A-II/apo B, apo A-I/apo B, apo B, total cholesterol, and LDL-cholesterol. A retrospective classification of patients and controls under optimal conditions with one variable (apo A-I/apo B) yielded an error rate of 25%. We found that apolipoproteins were better discriminators for peripheral atherosclerosis than than were lipids or lipoprotein lipids. The application of a linear regression discriminant analysis including 29 variables greatly decreased the rate of error and increased the sensitivity and specificity of the classification. From 229 possible models, we used an economic selection strategy to sort out those which either gave the best segregation or were considered the most practicable. The optimal model with 14 variables gave an error rate of less than 5% for the group studied. Suboptimal models yielded error rates between 13% and 18%. We conclude that a mathematical treatment of laboratory data which includes lipid parameters in addition to apolipoprotein values can improve the classification of peripheral vascular atherosclerosis.

Adult↗
PubMed2000

The role of discriminant analysis in the refinement of customer satisfaction assessment.

OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.

Discriminant Analysis↗
PubMed1982

Discriminant analysis of radiation therapy procedures: the Patterns of Care Process Survey for carcinoma of the larynx.

Discriminant analysis was applied to larynx data from the Patterns of Care Study (PCS) in order to evaluate and classify radiation therapy procedures. Since PCS has recorded information on a large number of separate procedures, a method was needed to treat them coherently. Discriminant analysis provided such a method through a comprehensive score of performance. The particular discriminant score used was calculated from the contrast between facilities with and without radiation therapy resident training programs. Because residents drastically affect the practice of radiation therapy in a facility, this factor provided a foundation for analyzing the procedures themselves. Results of the discriminant analysis were used to derive a condensed list of generalized procedural criteria which contains almost all the discrimination information of the original procedures and which elucidates their relative importance and the relations among them.

Evaluation Studies as Topic↗
PubMed2005

Improving model robustness with bootstrapping -- application to optimal discriminant analysis for ordinal responses (ODAO).

OBJECTIVE: Recent results published by Coste et al. in discriminant analysis with ordinal responses showed the superiority of optimal discriminating analysis for ordinal responses (ODAO) both in terms of classification and simplicity of implementation compared to classic methods (Fisher's discrimination, logistic regression) applied to medical data (prognostics of burns) and to simulated data. Nevertheless, the solutions obtained by ODAO may be sensitive to re-sampling (i.e the estimated coefficients by ODAO may show excessive sensitivity to the training sample). This study proposes some solutions to control the fluctuations of sampling and to ensure model stability. METHODS: We used intensive computational methods and bootstrapping, at the outset of model building in order to reduce the sampling variability of estimated coefficients. Thus, the estimation of the coefficients was not based on the minimization of a classification criterion of the training sample, but on the minimization of an aggregate criterion of bootstrapped replications of a classification criterion. Five aggregate criteria were studied. RESULTS: The improvement in terms of robustness appeared in 30% of the test cases with moderate training sample size and 55% of those with small training sample size. CONCLUSION: Simulated test cases showed that bootstrapping can help construct more robust models in difficult classification situations and small training samples which are particularly frequent.

Burns↗
PubMed1993

Identification of high-risk patients with left main and three-vessel coronary artery disease using stepwise discriminant analysis of clinical, exercise, and tomographic thallium data.

This large-scale study examined the ability of stepwise discriminant analysis of clinical, exercise, and thallium tomographic data to detect high-risk patients with three-vessel or left main disease. There were 834 patients, 229 with three-vessel or left main disease (group 1) and 605 (group 2) with either two-vessel disease (n = 236), one-vessel disease (n = 195), or no coronary artery disease (n = 174). The two groups were different in age, exercise heart rate, ST segment depression during exercise, exercise systolic blood pressure, abnormal thallium scans, reversible perfusion defects, extent of thallium abnormality, number of vascular territories with perfusion abnormalities, left ventricular cavity dilatation, and increased lung thallium uptake. On multivariate stepwise discriminant analysis, only three variables were independent predictors of high risk. These included multivessel thallium abnormality (F = 107, p < 0.001), exercise heart rate (F = 27, p < 0.001), and ST segment depression (F = 8, p < 0.01). Based on these three variables, patients could be stratified into three categories with different prevalences of left main or three-vessel disease; the prevalence was 53% in 239 patients, 24% in 271 patients, and 12% in 324 patients. Thus high-risk patients with left main or three-vessel disease can be identified by exercise thallium tomographic imaging that uses a model based on stepwise discriminant analysis. The thallium data are far more powerful than the clinical or treadmill exercise data.

Aged↗
PubMed1995

Discriminant analysis in treatment evaluation of ectopic eruption of the maxillary first permanent molars.

The value of an analytical routine which could be used in the evaluation of clinical studies was assessed. Stepwise discriminant analysis with stepwise selection/elimination was used to reduce the amount of data without losing information before further analyses with canonical discriminant analysis. The purpose of canonical discriminant analysis was to reveal interactions between factors associated with the ectopic eruption of the first permanent molars. Two canonical discriminant functions were used to determine the accuracy of diagnosis and the effect of treatment. This information consisted of variables which were the most important (their ranks) and their single correlations (structure coefficients) to the function itself. This information was interpreted clinically. The coefficients of the canonical discriminant functions can be used for classification purposes. The use of a scatterplot instead of simple classification tables is suggested. The scatterplot was particularly informative on how well the procedure discriminated between groups. A table based on original data is included to allow the reader to test the validity of the findings on cases of his/her own. This multivariate strategy avoids spurious intercorrelations between two or more variables analysed as multiple single factors that has a high risk of erroneous conclusions.

Child↗
PubMed1989

Discriminant analysis on the treatment results of interstitial radium tongue implants.

Discriminant analysis was carried out for 48 tongue cancer patients who were treated with radium single-plane implantation. The 48 patients were grouped into 32 successfully cured without complications, five successfully cured with complications, six successfully cured but requiring additional boost therapy and five with local recurrence. To evaluate the relation between the dose distribution and the local treatment results, the analysis was based on a volume-dose relationship. The functions introduced by this discriminant analysis were linear, and the parameters used were modal dose, average dose and shape factors of histograms. Each group of treatment results had a correction rate of greater than 80%, except for the successfully cured group with ulcers. The discriminant functions were useful as an index to obtain a final clinical treatment result at the early time of implantation, and these functions could be used as a criterion for the optimal treatment of tongue carcinoma. We were also able to recognize the limitation of the actual arrangement of sources in the single-plane implant.

Brachytherapy↗
PubMed1989

[Extraction and classification of features of experimental gingivitis. Discriminant analysis of TS 200 data sequences].

This paper represent one of the important index of gingival color to various conditions. Generally the gingival color is very difficult problem to measure, so experimental gingivitis has to be treated by special technique such as Discriminant Analysis in spectrum pattern analysing. On measuring gingiva, Standard Measuring System is used in our department. Tissue Spectrum Analyzer TS-200 is used for measuring gingival color and spectrum pattern. Spectrum patterns are classified by its strength into three categories, that is Normal, Slightly-Redness and Redness. Discriminant Analysis and Graph Analysis (Constellation Graph) showed each group of property. The following results were obtained; Spectrum patterns have two peaks, that is 542 nm and 577 nm. With gingivitis change on three steps, that is Normal, Slightly-Redness and Redness, spectrum powers and difference of absorption in spectrum degrees and brightness is down. With gingivitis change, the Z1 value was obtained by Discriminant Analysis and showed a tendency to sign change from minus to plus. In the result of Discriminant Analysis distinction rate is 97.4% in N Group, 98.5% in SR Group and 100% in R Group. Constellation Graph represented each group of property clearly.

Color↗
PubMed1989

Preventive distinction of patients with primary or secondary hypertension by discriminant analysis of chronobiologic parameters estimated on 24-hour blood pressure patterns.

This investigation deals with a statistical probatory that patients with primary (PH) or secondary (SH) hypertension may be correctly diagnosed by a discriminant analysis of the chronobiologic characteristics computed on the 24-hour blood pressure (BP) patterns. The methodology concerning non-invasive 24-h BP monitoring, chronobiologic analysis and the discrimination process is detailed. Substantial dissimilarities were found in the statistical distribution for systolic and diastolic BP rhythmometric parameters (mesor, amplitude and acrophase) by a retrospective assessment of two groups, consisting of 54 patients with PH and 16 patients with SH. The group-related distribution for rhythmometric parameters was found to be significantly different to generate a statistically significant intergroup discriminatory boundary. The discriminant analysis correctly diagnosed patients with PH and SH in a percentage of about 91% and 63%, respectively. The high incidence of success is convincing that the combination of 24-h BP monitoring/chronobiologic analysis/discrimination process cna be a practical tool for confidently selecting patients with a presumable PH or SH.

Adolescent↗
PubMed1981

Prediction of cerebellopontine angle tumors based on discriminant analysis of brain stem auditory evoked responses.

Multivariate discriminant analysis of brain stem auditory evoked response component latency intervals in patients with cerebellopontine angle tumors allowed accurate detection of 90% (35 of 39) of the tumor population with response data recordable from at least one ear. Eight-five per cent (23 of 27) of these could be detected by using information from the unaffected ear. One of 21 normal subjects was misclassified. Tumors significantly increased the I-III and III-V intervals on the side of the tumor. Increases in III-V interval latency were also observed on the unaffected side. The size of the tumor was significantly correlated with both discriminant scores derived from the analysis of the unaffected ear and delays in the III-V intervals from either the affected or the unaffected ear. These results were attributed to physiological factors and mechanical distortions of the brain stem. Regression equations derived from linear discriminant analysis for cerebellopontine angle tumors are presented and discussed in terms of their predictive validity.

Brain Neoplasms↗
PubMed1980

Hydrocortisone suppression test and discriminant analysis in differential diagnosis of hypercalcaemia.

Experience is reported of the hydrocortisone suppression test in 140 hypercalcaemic patients, comprising 98 new cases of hyperparathyroidism and 42 cases of non-parathyroid malignant disease. The diagnostic accuracy of the test was compared in 168 patients with that of discriminant analysis, the discriminant functions being derived from plasma inorganic phosphate, alkaline phosphatase, chloride, bicarbonate, and urea, and the erythrocyte sedimentation rate. The hydrocortisone test and discriminant analysis each achieved a diagnostic accuracy of about 93% in 148 patients with either non-parathyroid malignant disease or hyperparathyroidism without osteitis fibrosa. When both tests pointed to the same diagnosis, they were wrong in less than 1% of cases. The hydrocortisone test was not helpful in patients with osteitis fibrosa. Both tests can be performed in any hospital with reliable standard laboratory services. Used in combination they have a high predictive value in distinguishing hypercalcaemia of parathyroid origin from that due to non-parathyroid malignant disease and have not led to errors of clinical importance. They should continue to play a major role in the differential diagnosis of hypercalcaemia until a prompt and reliable service finally establishes parathyroid hormone assay as the definitive laboratory procedure.

Adult↗
PubMed2004

Application of stepwise discriminant analysis to classify commercial orange juices using chiral micellar electrokinetic chromatography-laser induced fluorescence data of amino acids.

The use of chiral amino acids content and stepwise discriminant analysis to classify three types of commercial orange juices (i.e., nectars, orange juices reconstituted from concentrates, and pasteurized orange juices not from concentrates) is presented. Micellar electrokinetic chromatography with laser-induced fluorescence (MEKC-LIF) and beta-cyclodextrins are used to determine L- and D-amino acids previously derivatized with fluorescein isothiocyanate (FITC). This chiral MEKC-LIF procedure is easy to implement and provides information about the main amino acids content in orange juices (i.e., L-proline; L-aspartic acid, D-Asp, L-serine, L-asparagine, L-glutamic acid, D-Glu, L-alanine, L-.arginine, D-Arg, and the non-chiral gamma-amino-n-butyric acid (GABA), i.e., gamma-aminobutyric acid). From these results, it is clearly demonstrated that some D-amino acids occur naturally in orange juices. Application of stepwise discriminant analysis to 26 standard samples showed that the amino acids L-Arg, L-Asp and GABA were the most important variables to differentiate the three groups of samples. With these three selected amino acids a 100% correct classification of the samples was obtained either by standard or by leave-one-out cross-validation procedures. These classification functions based on the content in L-Arg, L-Asp and GABA were also applied to nine test samples and provided an adequate classification and/or interesting information on these samples. It is concluded that chiral MEKC-LIF analysis of amino acids and stepwise discriminant analysis can be used as a consistent procedure to classify commercial orange juices providing useful information about their quality and processing. To our knowledge, this is the first report about the combined use of chiral capillary electrophoresis and discriminant techniques to classify foods.

Amino Acids↗
PubMed1987

Comparison of the ID3 algorithm versus discriminant analysis for performing feature selection.

Having obtained disappointing results in a small medical data set despite the fact that our data seemed to be well suited for induction via ID3, we decided to compare the performance of ID3 to discriminant analysis. Performance was gauged by the percentage of correct classification in a second, independent data set. Examples were obtained from a cardiology project on the accuracy of auscultation. There were 107 examples in the first data set and 67 cases in the second. We found that ID3 and discriminant analysis performed equally poorly, with ID3 classifying only 60% of the second set correctly and discriminant analysis classifying 66% of the second set correctly. Also, the ID3 probability statistic for estimating the accuracy of ID3 for classifying further cases was markedly optimistic compared to our actual second data set results. Moreover, with an increase in sample size, ID3 seemed to break down, producing a large, complex decision tree of dubious generality, whereas discriminant analysis, with a larger sample size, used more independent variables but maintained its first set accuracy. These data suggest that there is a need for more sophisticated algorithms than ID3, even at the risk of giving up some computational efficiency.

Adult↗
PubMed1994

The identification of Class III malocclusions by discriminant analysis.

Lateral cephalometric radiographs of 210 control and 285 Class III subjects were traced, digitized, and 43 calculated variables submitted to a stepwise discriminant analysis. A 10-factor model was generated, giving 95.2 per cent correct classification of the control children and 95.1 per cent accurate identification of the Class III group. Ten control and 14 Class III children were categorized incorrectly. To test the validity of the analysis, radiographs of these 24 individuals were examined in detail. In all cases, a satisfactory reason for the misgrouping was identified. This investigation underlined the importance of rigorous standards of case selection when compiling the groups. The robustness of the 10-factor model was also examined. Subjects were arbitrarily split into two groups, the odd- and the even-numbered cases, and the discriminant analysis repeated on each. Both new models contained the same 10 variables, but with slightly different values for their accompanying coefficients. The cases erroneously identified by the whole group analysis were again misclassified, together with a few additional cases. Each new model performed equally well on the data from the opposing group as on that from which it had been derived. Thus, the model generated in this study was both valid and acceptably robust. It would therefore appear that discriminant analysis may be a viable tool in the identification and classification of groups of individuals.

Adolescent↗
PubMedDate not supplied

Classification of ultrasonic image texture by statistical discriminant analysis of neutral networks.

In this paper the ability of two common statistical discriminant analysis procedures are compared with two commercial neural network software packages. The major objective of this study was to determine which of the procedures could best discriminate between normal and abnormal ultrasonic liver textures. The same set of features were input into both statistical discriminant analysis procedures and both neural network models. Preliminary results have found the restricted Coulomb Energy (RCE) neural network model to have a testing accuracy of 90.6% which is approximately 10% better than any of the other techniques investigated.

Algorithms↗