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298:. In binary classification, a better understood task, only two classes are involved, whereas multiclass classification involves assigning an object to one of several classes. Since many classification methods have been developed specifically for binary classification, multiclass classification often requires the combined use of multiple binary classifiers.
356:(e.g. a measurement of blood pressure). If the instance is an image, the feature values might correspond to the pixels of an image; if the instance is a piece of text, the feature values might be occurrence frequencies of different words. Some algorithms work only in terms of discrete data and require that real-valued or integer-valued data be
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Unlike frequentist procedures, Bayesian classification procedures provide a natural way of taking into account any available information about the relative sizes of the different groups within the overall population. Bayesian procedures tend to be computationally expensive and, in the days before
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of the instance being a member of each of the possible classes. The best class is normally then selected as the one with the highest probability. However, such an algorithm has numerous advantages over non-probabilistic classifiers:
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Because of the probabilities which are generated, probabilistic classifiers can be more effectively incorporated into larger machine-learning tasks, in a way that partially or completely avoids the problem of
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Since no single form of classification is appropriate for all data sets, a large toolkit of classification algorithms has been developed. The most commonly used include:
250:. The extension of this same context to more than two groups has also been considered with a restriction imposed that the classification rule should be
548:. What distinguishes them is the procedure for determining (training) the optimal weights/coefficients and the way that the score is interpreted.
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function as the rule for assigning a group to a new observation. This early work assumed that data-values within each of the two groups had a
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to find the best class for a given instance. Unlike other algorithms, which simply output a "best" class, probabilistic algorithms output a
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It can output a confidence value associated with its choice (in general, a classifier that can do this is known as a
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471:{\displaystyle \operatorname {score} (\mathbf {X} _{i},k)={\boldsymbol {\beta }}_{k}\cdot \mathbf {X} _{i},}
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73:). Other classifiers work by comparing observations to previous observations by means of a
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Most algorithms describe an individual instance whose category is to be predicted using a
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Advances in Neural
Information Processing Systems 15: Proceedings of the 2002 Conference
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computations were developed, approximations for
Bayesian clustering rules were devised.
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that implements classification, especially in a concrete implementation, is known as a
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258:: several classification rules can be derived based on different adjustments of the
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of individual, measurable properties of the instance. Each property is termed a
96:, implemented by a classification algorithm, that maps input data to a category.
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Fisher, R. A. (1936). "The Use of
Multiple Measurements in Taxonomic Problems".
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Fisher, R. A. (1938). "The
Statistical Utilization of Multiple Measurements".
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procedure, while in others more detailed statistical modeling is undertaken.
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170:, which assigns a class to each member of a sequence of values (for example,
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Classification has many applications. In some of these, it is employed as a
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Binder, David A. (1981). "Approximations to
Bayesian clustering rules".
690: â Method used in statistics, pattern recognition, and other fields
594: â Method used in statistics, pattern recognition, and other fields
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1056: â Obtaining information resources relevant to an information need
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into groups (e.g. less than 5, between 5 and 10, or greater than 10).
352:(e.g. the number of occurrences of a particular word in an email); or
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814: â Numerical expression representing a person's creditworthiness
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833: â Process of bringing a new pharmaceutical drug to the market
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the feature vector of an instance with a vector of weights, using a
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92:. The term "classifier" sometimes also refers to the mathematical
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Methods for
Statistical Data Analysis of Multivariate Observations
1073: â Information filtering system to predict users' preferences
1007: â Problem in machine learning and statistical classification
888: â Information filtering system to predict users' preferences
882: â Automated recognition of patterns and regularities in data
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or a similar procedure, the properties of observations are termed
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when its confidence of choosing any particular output is too low.
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711: â Algorithm for supervised learning of binary classifiers
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1312:"A Tour of The Top 10 Algorithms for Machine Learning Newbies"
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Classification can be thought of as two separate problems â
1423:
728: â Set of methods for supervised statistical learning
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Early work on statistical classification was undertaken by
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and clustering are examples of the more general problem of
61:(e.g. the number of occurrences of a particular word in an
859: â Branch of statistics focusing on spatial data sets
803: â finding the item in each frame of a video sequence
588: â Set of methods for supervised statistical learning
558: â Statistical model for a binary dependent variable
894: â Automatic conversion of spoken language into text
699: â Statistical model for a binary dependent variable
784: â Computerized information extraction from images
1015:
Pages displaying short descriptions of redirect targets
902:
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684: â Statistical classification in machine learning
670:
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285:
139:. Other fields may use different terminology: e.g. in
564: â Regression for more than two discrete outcomes
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Some
Bayesian procedures involve the calculation of
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Autoregressive conditional heteroskedasticity (ARCH)
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Pages displaying wikidata descriptions as a fallback
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Pages displaying wikidata descriptions as a fallback
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Pages displaying wikidata descriptions as a fallback
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Pages displaying wikidata descriptions as a fallback
166:, which assigns a real-valued output to each input;
1226:Binder, D. A. (1978). "Bayesian cluster analysis".
625: â Tree-based ensemble machine learning method
500:is the vector of weights corresponding to category
242:, in the context of two-group problems, leading to
135:), and the possible categories to be predicted are
2707:
517:) is the score associated with assigning instance
470:
900: â Field of linguistics and computer science
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774: â Metrics related to human characteristics
378:for classification can be phrased in terms of a
2793:Multivariate adaptive regression splines (MARS)
382:that assigns a score to each possible category
143:, the term "classification" normally refers to
1060:List of datasets for machine learning research
1001: â Dividing things between two categories
705: â Probabilistic classification algorithm
544:Algorithms with this basic setup are known as
99:Terminology across fields is quite varied. In
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648: â type of genetic programming algorithm
150:
1050: â System for reasoning about vagueness
846:Quantitative structure-activity relationship
668: â Non-parametric classification method
797: â Computer recognition of visual text
1393:
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103:, where classification is often done with
2006:
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1115:
957:Learn how and when to remove this message
839: â branch of toxicology and genomics
823: â Process of categorizing documents
233:
1044: â Centralized storage of knowledge
920:This article includes a list of general
1168:
1166:
898:Statistical natural language processing
440:
193:A common subclass of classification is
127:, the explanatory variables are termed
27:Categorization of data using statistics
14:
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3319:KaplanâMeier estimator (product limit)
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328:, although features may or may not be
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123:, the observations are often known as
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2005:
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348:(e.g. "large", "medium" or "small");
186:to an input sentence, describing the
57:(e.g. "large", "medium" or "small"),
45:. These properties may variously be
3629:
3329:Accelerated failure time (AFT) model
1163:
906:
753:Cluster analysis § Applications
732:Least squares support vector machine
551:Examples of such algorithms include
398:and has the following general form:
286:Binary and multiclass classification
178:to each word in an input sentence);
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2924:Analysis of variance (ANOVA, anova)
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487:is the feature vector for instance
24:
3019:CochranâMantelâHaenszel statistics
1645:Pearson product-moment correlation
1147:10.1111/j.1469-1809.1938.tb02189.x
1108:10.1111/j.1469-1809.1936.tb02137.x
926:it lacks sufficient corresponding
619: â Method in machine learning
301:
25:
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848: â Predictive chemical model
340:(e.g. "A", "B", "AB" or "O", for
320:, also known in statistics as an
197:. Algorithms of this nature use
49:(e.g. "A", "B", "AB" or "O", for
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1013: â Machine learning problem
995: â Intelligence of machines
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248:multivariate normal distribution
3278:Least-squares spectral analysis
562:Multinomial logistic regression
2259:Mean-unbiased minimum-variance
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1011:Class membership probabilities
637: â Evolutionary algorithm
432:
411:
332:). Features may variously be
280:group-membership probabilities
212:confidence-weighted classifier
13:
1:
3572:Geographic information system
2788:Simultaneous equations models
1078:
795:Optical character recognition
598:
2755:Coefficient of determination
2366:Uniformly most powerful test
688:Fisher's linear discriminant
677:Learning vector quantization
641:Multi expression programming
592:Linear discriminant analysis
244:Fisher's linear discriminant
195:probabilistic classification
7:
3324:Proportional hazards models
3268:Spectral density estimation
3250:Vector autoregression (VAR)
2684:Maximum posterior estimator
1916:Randomized controlled trial
969:
787:Medical image analysis and
635:Gene expression programming
617:Boosting (machine learning)
10:
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3669:Statistical classification
3084:Multivariate distributions
1504:Average absolute deviation
875:Micro-array classification
750:
646:Linear genetic programming
608:Artificial neural networks
367:
305:
151:Relation to other problems
3674:Classification algorithms
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1005:Multiclass classification
766:Biological classification
396:linear predictor function
330:statistically independent
296:multiclass classification
3567:Environmental statistics
3089:Elliptical distributions
2882:Generalized linear model
2811:Simple linear regression
2581:HodgesâLehmann estimator
2038:Probability distribution
1947:Stochastic approximation
1509:Coefficient of variation
1172:Gnanadesikan, R. (1977)
1025:Compound term processing
273:Markov chain Monte Carlo
217:Correspondingly, it can
18:Classifier (mathematics)
3227:Cross-correlation (XCF)
2835:Non-standard predictors
2269:LehmannâScheffĂ© theorem
1942:Adaptive clinical trial
1271:10.1093/biomet/68.1.275
993:Artificial intelligence
941:more precise citations.
863:Handwriting recognition
821:Document classification
659: â Window function
533:associated with person
69:(e.g. a measurement of
3623:Mathematics portal
3444:Engineering statistics
3352:NelsonâAalen estimator
2929:Analysis of covariance
2816:Ordinary least squares
2740:Pearson product-moment
2144:Statistical functional
2055:Empirical distribution
1888:Controlled experiments
1617:Frequency distribution
1395:Descriptive statistics
1290:, Obermayer, K. (Eds)
1242:10.1093/biomet/65.1.31
741:evaluation of accuracy
726:Support vector machine
703:Naive Bayes classifier
586:Support vector machine
472:
336:(e.g. "on" or "off");
234:Frequentist procedures
190:of the sentence; etc.
172:part of speech tagging
3539:Population statistics
3481:System identification
3215:Autocorrelation (ACF)
3143:Exponential smoothing
3057:Discriminant analysis
3052:Canonical correlation
2916:Partition of variance
2778:Regression validation
2622:(JonckheereâTerpstra)
2521:Likelihood-ratio test
2210:Frequentist inference
2122:Locationâscale family
2043:Sampling distribution
2008:Statistical inference
1975:Cross-sectional study
1962:Observational studies
1921:Randomized experiment
1750:Stem-and-leaf display
1552:Central limit theorem
1200:, Wiley. (Section 9c)
1054:Information retrieval
999:Binary classification
473:
292:binary classification
199:statistical inference
113:independent variables
109:explanatory variables
39:explanatory variables
3462:Probabilistic design
3047:Principal components
2890:Exponential families
2842:Nonlinear regression
2821:General linear model
2783:Mixed effects models
2773:Errors and residuals
2750:Confounding variable
2652:Bayesian probability
2630:Van der Waerden test
2620:Ordered alternative
2385:Multiple comparisons
2264:RaoâBlackwellization
2227:Estimating equations
2183:Statistical distance
1901:Factorial experiment
1434:Arithmetic-Geometric
717:Quadratic classifier
402:
326:independent variable
322:explanatory variable
260:Mahalanobis distance
3534:Official statistics
3457:Methods engineering
3138:Seasonal adjustment
2906:Poisson regressions
2826:Bayesian regression
2765:Regression analysis
2745:Partial correlation
2717:Regression analysis
2316:Prediction interval
2311:Likelihood interval
2301:Confidence interval
2293:Interval estimation
2254:Unbiased estimators
2072:Model specification
1952:Up-and-down designs
1640:Partial correlation
1596:Index of dispersion
1514:Interquartile range
1020:Classification rule
880:Pattern recognition
747:Application domains
697:Logistic regression
629:Genetic programming
556:Logistic regression
266:Bayesian procedures
188:syntactic structure
160:pattern recognition
105:logistic regression
3554:Spatial statistics
3434:Medical statistics
3334:First hitting time
3288:Whittle likelihood
2939:Degrees of freedom
2934:Multivariate ANOVA
2867:Heteroscedasticity
2679:Bayesian estimator
2644:Bayesian inference
2493:KolmogorovâSmirnov
2378:Randomization test
2348:Testing hypotheses
2321:Tolerance interval
2232:Maximum likelihood
2127:Exponential family
2060:Density estimation
2020:Statistical theory
1980:Natural experiment
1926:Scientific control
1843:Survey methodology
1529:Standard deviation
1134:Annals of Eugenics
1095:Annals of Eugenics
1071:Recommender system
984:Mathematics portal
892:Speech recognition
886:Recommender system
666:k-nearest neighbor
546:linear classifiers
537:choosing category
468:
374:A large number of
364:Linear classifiers
182:, which assigns a
174:, which assigns a
117:dependent variable
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3529:National accounts
3499:Actuarial science
3491:Social statistics
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2999:Contingency table
2974:Survival analysis
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2669:Credible interval
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2237:Method of moments
2106:Parametric family
2067:Statistical model
1997:
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1911:Random assignment
1833:Statistical power
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1612:Contingency table
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1449:Generalized/power
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682:Linear classifier
657:Kernel estimation
570:Probit regression
370:Linear classifier
227:error propagation
168:sequence labeling
141:community ecology
16:(Redirected from
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3273:Fourier analysis
3260:Frequency domain
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3153:Structural break
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3062:Cluster analysis
3009:Log-linear model
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2498:AndersonâDarling
2445:
2432:
2431:
2403:Likelihood-ratio
2395:Parametric tests
2373:Permutation test
2356:1- & 2-tails
2247:Minimum distance
2219:Point estimation
2215:
2214:
2166:Optimal decision
2117:
2016:
2015:
2003:
2002:
1985:Quasi-experiment
1935:Adaptive designs
1786:
1785:
1773:
1772:
1650:Rank correlation
1412:
1411:
1403:
1402:
1390:
1389:
1357:
1350:
1343:
1334:
1333:
1327:
1326:
1324:
1323:
1308:
1302:
1281:
1275:
1274:
1252:
1246:
1245:
1223:
1217:
1207:
1201:
1191:
1185:
1184:(p. 83–86)
1170:
1161:
1160:
1158:
1128:
1122:
1121:
1119:
1089:
1065:Machine learning
1030:Confusion matrix
1016:
986:
981:
980:
962:
955:
951:
948:
942:
937:this article by
928:inline citations
915:
914:
907:
903:
851:
842:
817:
806:
777:
722:
693:
671:
662:
651:
613:
575:
477:
475:
474:
469:
464:
463:
458:
449:
448:
443:
425:
424:
419:
145:cluster analysis
131:(grouped into a
121:machine learning
21:
3689:
3688:
3684:
3683:
3682:
3680:
3679:
3678:
3659:
3658:
3657:
3652:
3615:
3586:
3548:
3485:
3471:quality control
3438:
3420:Clinical trials
3397:
3372:
3356:
3344:Hazard function
3338:
3292:
3254:
3238:
3201:
3197:BreuschâGodfrey
3185:
3162:
3102:
3077:Factor analysis
3023:
3004:Graphical model
2976:
2943:
2910:
2896:
2876:
2830:
2797:
2759:
2722:
2721:
2690:
2634:
2621:
2613:
2605:
2589:
2574:
2553:Rank statistics
2547:
2526:Model selection
2514:
2472:Goodness of fit
2466:
2443:
2417:
2389:
2342:
2287:
2276:Median unbiased
2204:
2115:
2048:Order statistic
2010:
1989:
1956:
1930:
1882:
1837:
1780:
1778:Data collection
1759:
1671:
1626:
1600:
1578:
1538:
1490:
1407:Continuous data
1397:
1384:
1366:
1361:
1331:
1330:
1321:
1319:
1310:
1309:
1305:
1282:
1278:
1253:
1249:
1224:
1220:
1208:
1204:
1192:
1188:
1171:
1164:
1129:
1125:
1090:
1086:
1081:
1076:
1014:
982:
975:
972:
963:
952:
946:
943:
933:Please help to
932:
916:
912:
901:
849:
840:
815:
804:
789:medical imaging
782:Computer vision
775:
755:
749:
720:
691:
669:
660:
649:
611:
601:
573:
527:discrete choice
512:
499:
486:
459:
454:
453:
444:
439:
438:
420:
415:
414:
403:
400:
399:
380:linear function
372:
366:
310:
304:
302:Feature vectors
288:
268:
236:
153:
28:
23:
22:
15:
12:
11:
5:
3687:
3677:
3676:
3671:
3654:
3653:
3651:
3650:
3638:
3626:
3612:
3599:
3596:
3595:
3592:
3591:
3588:
3587:
3585:
3584:
3579:
3574:
3569:
3564:
3558:
3556:
3550:
3549:
3547:
3546:
3541:
3536:
3531:
3526:
3521:
3516:
3511:
3506:
3501:
3495:
3493:
3487:
3486:
3484:
3483:
3478:
3473:
3464:
3459:
3454:
3448:
3446:
3440:
3439:
3437:
3436:
3431:
3426:
3417:
3415:Bioinformatics
3411:
3409:
3399:
3398:
3386:
3385:
3382:
3381:
3378:
3377:
3374:
3373:
3371:
3370:
3364:
3362:
3358:
3357:
3355:
3354:
3348:
3346:
3340:
3339:
3337:
3336:
3331:
3326:
3321:
3315:
3313:
3304:
3298:
3297:
3294:
3293:
3291:
3290:
3285:
3280:
3275:
3270:
3264:
3262:
3256:
3255:
3253:
3252:
3247:
3242:
3234:
3229:
3224:
3223:
3222:
3220:partial (PACF)
3211:
3209:
3203:
3202:
3200:
3199:
3194:
3189:
3181:
3176:
3170:
3168:
3167:Specific tests
3164:
3163:
3161:
3160:
3155:
3150:
3145:
3140:
3135:
3130:
3125:
3119:
3117:
3110:
3104:
3103:
3101:
3100:
3099:
3098:
3097:
3096:
3081:
3080:
3079:
3069:
3067:Classification
3064:
3059:
3054:
3049:
3044:
3039:
3033:
3031:
3025:
3024:
3022:
3021:
3016:
3014:McNemar's test
3011:
3006:
3001:
2996:
2990:
2988:
2978:
2977:
2953:
2952:
2949:
2948:
2945:
2944:
2942:
2941:
2936:
2931:
2926:
2920:
2918:
2912:
2911:
2909:
2908:
2892:
2886:
2884:
2878:
2877:
2875:
2874:
2869:
2864:
2859:
2854:
2852:Semiparametric
2849:
2844:
2838:
2836:
2832:
2831:
2829:
2828:
2823:
2818:
2813:
2807:
2805:
2799:
2798:
2796:
2795:
2790:
2785:
2780:
2775:
2769:
2767:
2761:
2760:
2758:
2757:
2752:
2747:
2742:
2736:
2734:
2724:
2723:
2720:
2719:
2714:
2708:
2700:
2699:
2696:
2695:
2692:
2691:
2689:
2688:
2687:
2686:
2676:
2671:
2666:
2665:
2664:
2659:
2648:
2646:
2640:
2639:
2636:
2635:
2633:
2632:
2627:
2626:
2625:
2617:
2609:
2593:
2590:(MannâWhitney)
2585:
2584:
2583:
2570:
2569:
2568:
2557:
2555:
2549:
2548:
2546:
2545:
2544:
2543:
2538:
2533:
2523:
2518:
2515:(ShapiroâWilk)
2510:
2505:
2500:
2495:
2490:
2482:
2476:
2474:
2468:
2467:
2465:
2464:
2456:
2447:
2435:
2429:
2427:Specific tests
2423:
2422:
2419:
2418:
2416:
2415:
2410:
2405:
2399:
2397:
2391:
2390:
2388:
2387:
2382:
2381:
2380:
2370:
2369:
2368:
2358:
2352:
2350:
2344:
2343:
2341:
2340:
2339:
2338:
2333:
2323:
2318:
2313:
2308:
2303:
2297:
2295:
2289:
2288:
2286:
2285:
2280:
2279:
2278:
2273:
2272:
2271:
2266:
2251:
2250:
2249:
2244:
2239:
2234:
2223:
2221:
2212:
2206:
2205:
2203:
2202:
2197:
2192:
2191:
2190:
2180:
2175:
2174:
2173:
2163:
2162:
2161:
2156:
2151:
2141:
2136:
2131:
2130:
2129:
2124:
2119:
2103:
2102:
2101:
2096:
2091:
2081:
2080:
2079:
2074:
2064:
2063:
2062:
2052:
2051:
2050:
2040:
2035:
2030:
2024:
2022:
2012:
2011:
1999:
1998:
1995:
1994:
1991:
1990:
1988:
1987:
1982:
1977:
1972:
1966:
1964:
1958:
1957:
1955:
1954:
1949:
1944:
1938:
1936:
1932:
1931:
1929:
1928:
1923:
1918:
1913:
1908:
1903:
1898:
1892:
1890:
1884:
1883:
1881:
1880:
1878:Standard error
1875:
1870:
1865:
1864:
1863:
1858:
1847:
1845:
1839:
1838:
1836:
1835:
1830:
1825:
1820:
1815:
1810:
1808:Optimal design
1805:
1800:
1794:
1792:
1782:
1781:
1769:
1768:
1765:
1764:
1761:
1760:
1758:
1757:
1752:
1747:
1742:
1737:
1732:
1727:
1722:
1717:
1712:
1707:
1702:
1697:
1692:
1687:
1681:
1679:
1673:
1672:
1670:
1669:
1664:
1663:
1662:
1657:
1647:
1642:
1636:
1634:
1628:
1627:
1625:
1624:
1619:
1614:
1608:
1606:
1605:Summary tables
1602:
1601:
1599:
1598:
1592:
1590:
1584:
1583:
1580:
1579:
1577:
1576:
1575:
1574:
1569:
1564:
1554:
1548:
1546:
1540:
1539:
1537:
1536:
1531:
1526:
1521:
1516:
1511:
1506:
1500:
1498:
1492:
1491:
1489:
1488:
1483:
1478:
1477:
1476:
1471:
1466:
1461:
1456:
1451:
1446:
1441:
1439:Contraharmonic
1436:
1431:
1420:
1418:
1409:
1399:
1398:
1386:
1385:
1383:
1382:
1377:
1371:
1368:
1367:
1360:
1359:
1352:
1345:
1337:
1329:
1328:
1303:
1276:
1247:
1218:
1210:Anderson, T.W.
1202:
1186:
1162:
1141:(4): 376â386.
1123:
1102:(2): 179â188.
1083:
1082:
1080:
1077:
1075:
1074:
1068:
1062:
1057:
1051:
1045:
1042:Data warehouse
1039:
1033:
1027:
1022:
1017:
1008:
1002:
996:
989:
988:
987:
971:
968:
965:
964:
919:
917:
910:
905:
904:
895:
889:
883:
877:
872:
870:search engines
866:
860:
854:
853:
852:
843:
837:Toxicogenomics
827:Drug discovery
824:
818:
812:Credit scoring
809:
808:
807:
801:Video tracking
798:
792:
779:
778:identification
769:
748:
745:
737:
736:
735:
734:
723:
714:
713:
712:
706:
700:
694:
679:
674:
673:
672:
654:
653:
652:
643:
638:
626:
620:
614:
600:
597:
596:
595:
589:
583:
576:
567:
566:
565:
508:
495:
482:
467:
462:
457:
452:
447:
442:
437:
434:
431:
428:
423:
418:
413:
410:
407:
368:Main article:
365:
362:
350:integer-valued
314:feature vector
308:Feature vector
306:Main article:
303:
300:
287:
284:
267:
264:
235:
232:
231:
230:
222:
215:
176:part of speech
156:Classification
152:
149:
133:feature vector
71:blood pressure
59:integer-valued
32:classification
26:
9:
6:
4:
3:
2:
3686:
3675:
3672:
3670:
3667:
3666:
3664:
3649:
3648:
3639:
3637:
3636:
3627:
3625:
3624:
3619:
3613:
3611:
3610:
3601:
3600:
3597:
3583:
3580:
3578:
3577:Geostatistics
3575:
3573:
3570:
3568:
3565:
3563:
3560:
3559:
3557:
3555:
3551:
3545:
3544:Psychometrics
3542:
3540:
3537:
3535:
3532:
3530:
3527:
3525:
3522:
3520:
3517:
3515:
3512:
3510:
3507:
3505:
3502:
3500:
3497:
3496:
3494:
3492:
3488:
3482:
3479:
3477:
3474:
3472:
3468:
3465:
3463:
3460:
3458:
3455:
3453:
3450:
3449:
3447:
3445:
3441:
3435:
3432:
3430:
3427:
3425:
3421:
3418:
3416:
3413:
3412:
3410:
3408:
3407:Biostatistics
3404:
3400:
3396:
3391:
3387:
3369:
3368:Log-rank test
3366:
3365:
3363:
3359:
3353:
3350:
3349:
3347:
3345:
3341:
3335:
3332:
3330:
3327:
3325:
3322:
3320:
3317:
3316:
3314:
3312:
3308:
3305:
3303:
3299:
3289:
3286:
3284:
3281:
3279:
3276:
3274:
3271:
3269:
3266:
3265:
3263:
3261:
3257:
3251:
3248:
3246:
3243:
3241:
3239:(BoxâJenkins)
3235:
3233:
3230:
3228:
3225:
3221:
3218:
3217:
3216:
3213:
3212:
3210:
3208:
3204:
3198:
3195:
3193:
3192:DurbinâWatson
3190:
3188:
3182:
3180:
3177:
3175:
3174:DickeyâFuller
3172:
3171:
3169:
3165:
3159:
3156:
3154:
3151:
3149:
3148:Cointegration
3146:
3144:
3141:
3139:
3136:
3134:
3131:
3129:
3126:
3124:
3123:Decomposition
3121:
3120:
3118:
3114:
3111:
3109:
3105:
3095:
3092:
3091:
3090:
3087:
3086:
3085:
3082:
3078:
3075:
3074:
3073:
3070:
3068:
3065:
3063:
3060:
3058:
3055:
3053:
3050:
3048:
3045:
3043:
3040:
3038:
3035:
3034:
3032:
3030:
3026:
3020:
3017:
3015:
3012:
3010:
3007:
3005:
3002:
3000:
2997:
2995:
2994:Cohen's kappa
2992:
2991:
2989:
2987:
2983:
2979:
2975:
2971:
2967:
2963:
2958:
2954:
2940:
2937:
2935:
2932:
2930:
2927:
2925:
2922:
2921:
2919:
2917:
2913:
2907:
2903:
2899:
2893:
2891:
2888:
2887:
2885:
2883:
2879:
2873:
2870:
2868:
2865:
2863:
2860:
2858:
2855:
2853:
2850:
2848:
2847:Nonparametric
2845:
2843:
2840:
2839:
2837:
2833:
2827:
2824:
2822:
2819:
2817:
2814:
2812:
2809:
2808:
2806:
2804:
2800:
2794:
2791:
2789:
2786:
2784:
2781:
2779:
2776:
2774:
2771:
2770:
2768:
2766:
2762:
2756:
2753:
2751:
2748:
2746:
2743:
2741:
2738:
2737:
2735:
2733:
2729:
2725:
2718:
2715:
2713:
2710:
2709:
2705:
2701:
2685:
2682:
2681:
2680:
2677:
2675:
2672:
2670:
2667:
2663:
2660:
2658:
2655:
2654:
2653:
2650:
2649:
2647:
2645:
2641:
2631:
2628:
2624:
2618:
2616:
2610:
2608:
2602:
2601:
2600:
2597:
2596:Nonparametric
2594:
2592:
2586:
2582:
2579:
2578:
2577:
2571:
2567:
2566:Sample median
2564:
2563:
2562:
2559:
2558:
2556:
2554:
2550:
2542:
2539:
2537:
2534:
2532:
2529:
2528:
2527:
2524:
2522:
2519:
2517:
2511:
2509:
2506:
2504:
2501:
2499:
2496:
2494:
2491:
2489:
2487:
2483:
2481:
2478:
2477:
2475:
2473:
2469:
2463:
2461:
2457:
2455:
2453:
2448:
2446:
2441:
2437:
2436:
2433:
2430:
2428:
2424:
2414:
2411:
2409:
2406:
2404:
2401:
2400:
2398:
2396:
2392:
2386:
2383:
2379:
2376:
2375:
2374:
2371:
2367:
2364:
2363:
2362:
2359:
2357:
2354:
2353:
2351:
2349:
2345:
2337:
2334:
2332:
2329:
2328:
2327:
2324:
2322:
2319:
2317:
2314:
2312:
2309:
2307:
2304:
2302:
2299:
2298:
2296:
2294:
2290:
2284:
2281:
2277:
2274:
2270:
2267:
2265:
2262:
2261:
2260:
2257:
2256:
2255:
2252:
2248:
2245:
2243:
2240:
2238:
2235:
2233:
2230:
2229:
2228:
2225:
2224:
2222:
2220:
2216:
2213:
2211:
2207:
2201:
2198:
2196:
2193:
2189:
2186:
2185:
2184:
2181:
2179:
2176:
2172:
2171:loss function
2169:
2168:
2167:
2164:
2160:
2157:
2155:
2152:
2150:
2147:
2146:
2145:
2142:
2140:
2137:
2135:
2132:
2128:
2125:
2123:
2120:
2118:
2112:
2109:
2108:
2107:
2104:
2100:
2097:
2095:
2092:
2090:
2087:
2086:
2085:
2082:
2078:
2075:
2073:
2070:
2069:
2068:
2065:
2061:
2058:
2057:
2056:
2053:
2049:
2046:
2045:
2044:
2041:
2039:
2036:
2034:
2031:
2029:
2026:
2025:
2023:
2021:
2017:
2013:
2009:
2004:
2000:
1986:
1983:
1981:
1978:
1976:
1973:
1971:
1968:
1967:
1965:
1963:
1959:
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1300:0-262-02550-7
1297:
1294:, MIT Press.
1293:
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1284:Har-Peled, S.
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857:Geostatistics
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3607:
3519:Econometrics
3469: /
3452:Chemometrics
3429:Epidemiology
3422: /
3395:Applications
3237:ARIMA model
3184:Q-statistic
3133:Stationarity
3066:
3029:Multivariate
2972: /
2968: /
2966:Multivariate
2964: /
2904: /
2900: /
2674:Bayes factor
2573:Signed rank
2485:
2459:
2451:
2439:
2134:Completeness
1970:Cohort study
1868:Opinion poll
1803:Missing data
1790:Study design
1745:Scatter plot
1667:Scatter plot
1660:Spearman's Ï
1622:Grouped data
1320:. Retrieved
1318:. 2018-01-20
1315:
1306:
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1279:
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1213:
1205:
1197:
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1138:
1132:
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1093:
1087:
953:
947:January 2010
944:
925:
756:
738:
602:
550:
543:
538:
534:
522:
521:to category
518:
514:
509:
505:
504:, and score(
501:
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488:
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383:
373:
357:
311:
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154:
136:
128:
124:
98:
89:
83:
42:
36:
29:
3647:WikiProject
3562:Cartography
3524:Jurimetrics
3476:Reliability
3207:Time domain
3186:(LjungâBox)
3108:Time-series
2986:Categorical
2970:Time-series
2962:Categorical
2897:(Bernoulli)
2732:Correlation
2712:Correlation
2508:JarqueâBera
2480:Chi-squared
2242:M-estimator
2195:Asymptotics
2139:Sufficiency
1906:Interaction
1818:Replication
1798:Effect size
1755:Violin plot
1735:Radar chart
1715:Forest plot
1705:Correlogram
1655:Kendall's Ï
1265:: 275â285.
1048:Fuzzy logic
1036:Data mining
939:introducing
831:development
759:data mining
392:dot product
358:discretized
354:real-valued
338:categorical
203:probability
67:real-valued
47:categorical
3663:Categories
3514:Demography
3232:ARMA model
3037:Regression
2614:(Friedman)
2575:(Wilcoxon)
2513:Normality
2503:Lilliefors
2450:Student's
2326:Resampling
2200:Robustness
2188:divergence
2178:Efficiency
2116:(monotone)
2111:Likelihood
2028:Population
1861:Stratified
1813:Population
1632:Dependence
1588:Count data
1519:Percentile
1496:Dispersion
1429:Arithmetic
1364:Statistics
1322:2019-06-10
1258:Biometrika
1229:Biometrika
1156:2440/15232
1117:2440/15227
1079:References
922:references
751:See also:
709:Perceptron
599:Algorithms
580:perceptron
376:algorithms
342:blood type
184:parse tree
164:regression
101:statistics
90:classifier
81:function.
75:similarity
51:blood type
2895:Logistic
2662:posterior
2588:Rank sum
2336:Jackknife
2331:Bootstrap
2149:Bootstrap
2084:Parameter
2033:Statistic
1828:Statistic
1740:Run chart
1725:Pie chart
1720:Histogram
1710:Fan chart
1685:Bar chart
1567:L-moments
1454:Geometric
1288:Thrun, S.
1236:: 31â38.
1194:Rao, C.R.
1176:, Wiley.
868:Internet
772:Biometric
582:algorithm
451:⋅
441:β
409:
388:combining
256:nonlinear
125:instances
86:algorithm
3609:Category
3302:Survival
3179:Johansen
2902:Binomial
2857:Isotonic
2444:(normal)
2089:location
1896:Blocking
1851:Sampling
1730:QâQ plot
1695:Box plot
1677:Graphics
1572:Skewness
1562:Kurtosis
1534:Variance
1464:Heronian
1459:Harmonic
1316:Built In
1216:, Wiley.
970:See also
129:features
94:function
79:distance
43:features
3635:Commons
3582:Kriging
3467:Process
3424:studies
3283:Wavelet
3116:General
2283:Plug-in
2077:L space
1856:Cluster
1557:Moments
1375:Outline
1212:(1958)
1196:(1952)
935:improve
531:utility
346:ordinal
318:feature
219:abstain
180:parsing
137:classes
55:ordinal
3504:Census
3094:Normal
3042:Manova
2862:Robust
2612:2-way
2604:1-way
2442:-test
2113:
1690:Biplot
1481:Median
1474:Lehmer
1416:Center
1298:
1180:
924:, but
525:. In
478:where
334:binary
252:linear
240:Fisher
119:. In
3128:Trend
2657:prior
2599:anova
2488:-test
2462:-test
2454:-test
2361:Power
2306:Pivot
2099:shape
2094:scale
1544:Shape
1524:Range
1469:Heinz
1444:Cubic
1380:Index
406:score
65:) or
63:email
30:When
3361:Test
2561:Sign
2413:Wald
1486:Mode
1424:Mean
1296:ISBN
1178:ISBN
829:and
578:The
324:(or
294:and
111:(or
2541:BIC
2536:AIC
1267:doi
1238:doi
1151:hdl
1143:doi
1112:hdl
1104:doi
386:by
344:);
84:An
77:or
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