Latent class models for clustering: A comparison with K
... should be optimal according to some criteria. These criteria typically involve minimizing the within-cluster variation or, equivalently, maximizing the between-cluster variation. An advantage of using a statistical model is that the choice of the cluster criterion is less arbitrary and the approach ...
... should be optimal according to some criteria. These criteria typically involve minimizing the within-cluster variation or, equivalently, maximizing the between-cluster variation. An advantage of using a statistical model is that the choice of the cluster criterion is less arbitrary and the approach ...
Reducing the Number of Decision Variables in Ready Mixed
... higher than for the ones in the first category. Furthermore, the introduction of time restrictions on the schedule of trucks requires additional variables. In this paper, a new model for the single depot RMC dispatching problem is presented. The main contribution of this approach is to reduce the nu ...
... higher than for the ones in the first category. Furthermore, the introduction of time restrictions on the schedule of trucks requires additional variables. In this paper, a new model for the single depot RMC dispatching problem is presented. The main contribution of this approach is to reduce the nu ...
Probability Models for the NCAA Regional Basketball Tournaments
... distort the chi-square values. Hence a second set of chisquare statistics based on just the 26 seed pairings with at least 5 games was computed and is also given in Table 1. Models 1-8 use the data to estimate the model parameters, and consequently these chi-square values are not entirely independen ...
... distort the chi-square values. Hence a second set of chisquare statistics based on just the 26 seed pairings with at least 5 games was computed and is also given in Table 1. Models 1-8 use the data to estimate the model parameters, and consequently these chi-square values are not entirely independen ...
CSC2515: Lecture 10 Sequential Data
... that model will spend D steps in state k and then transition out: - instead associate distribution with time spent in state k: P(t|k) (see semi-Markov models for sequence segmentation applications) 2. Combine with auto-regressive Markov model: - include long-range relationships - directly model rela ...
... that model will spend D steps in state k and then transition out: - instead associate distribution with time spent in state k: P(t|k) (see semi-Markov models for sequence segmentation applications) 2. Combine with auto-regressive Markov model: - include long-range relationships - directly model rela ...
Exchangeability - Collegio Carlo Alberto
... mixing proportion is a transition probability • Use Bayesian nonparametric tools to allow the cardinality of the state space to be random – urn model point of view (Beal, et al, “infinite HMM”) – Dirichlet process point of view (Teh, et al, “HDP-HMM”) ...
... mixing proportion is a transition probability • Use Bayesian nonparametric tools to allow the cardinality of the state space to be random – urn model point of view (Beal, et al, “infinite HMM”) – Dirichlet process point of view (Teh, et al, “HDP-HMM”) ...
Neustar PlatformOne Solution Sheet
... Neustar helps to solve important marketing challenges: a complex marketing ecosystem, rapid consumer changes and the tsunami of data engulfing marketers today. Our centralized solution, PlatformOne, gives you a complete, real-time portrait of your customer based on accurate data, enabling a personal ...
... Neustar helps to solve important marketing challenges: a complex marketing ecosystem, rapid consumer changes and the tsunami of data engulfing marketers today. Our centralized solution, PlatformOne, gives you a complete, real-time portrait of your customer based on accurate data, enabling a personal ...
Temporal Data Models
... Time support in conventional DBs is only user-defined time: Date, Time, Timestamp Table I (temporal relational data models): – 14 “valid time” models – 3 “transaction time” models – 9 “valid and transaction time” models ...
... Time support in conventional DBs is only user-defined time: Date, Time, Timestamp Table I (temporal relational data models): – 14 “valid time” models – 3 “transaction time” models – 9 “valid and transaction time” models ...
Package `bstats`
... The Durbin-Watson test has the null hypothesis that the autocorrelation of the disturbances is 0. It is possible to test against the alternative that it is greater than, not equal to, or less than 0, respectively. This can be specified by the alternative argument. Under the assumption of normally di ...
... The Durbin-Watson test has the null hypothesis that the autocorrelation of the disturbances is 0. It is possible to test against the alternative that it is greater than, not equal to, or less than 0, respectively. This can be specified by the alternative argument. Under the assumption of normally di ...
General Introduction to SPSS
... • Categorical Variables = variables that have values which fall into two or more discrete categories – E.g. conventional light switch: either total darkness or full brightness, on or off. – Male or female, employment category, country of origin ...
... • Categorical Variables = variables that have values which fall into two or more discrete categories – E.g. conventional light switch: either total darkness or full brightness, on or off. – Male or female, employment category, country of origin ...
PDF
... behavior is concerned, while preferences, and associated behavior, across different subpopulations/segments are assumed statistically different. We utilize market segmentation techniques in the context of contingent valuation (CV). The CV method has become an important tool in environmental economic ...
... behavior is concerned, while preferences, and associated behavior, across different subpopulations/segments are assumed statistically different. We utilize market segmentation techniques in the context of contingent valuation (CV). The CV method has become an important tool in environmental economic ...
On Recognizing Music Using HMM
... Update the observation probability distribution with attributes of the vector and the state transition matrix by counting frequency of vectors being in a state ...
... Update the observation probability distribution with attributes of the vector and the state transition matrix by counting frequency of vectors being in a state ...
A Program demonstrating Gini Index Classification
... One of the attributes, called the classifying attribute, indicates the class to which each example belongs. The objective of classification is to build a model of the classifying attribute based upon the other attributes. Once a model is built, it can be used to determine the class of future unclass ...
... One of the attributes, called the classifying attribute, indicates the class to which each example belongs. The objective of classification is to build a model of the classifying attribute based upon the other attributes. Once a model is built, it can be used to determine the class of future unclass ...
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Bayesian Adaptative Methods for Clinical Trials [DOC 20KB]
... A clinical trial is a research study conducted to assess the utility of an intervention in volunteers and, in general, it provides the evidence to support regulatory approval of a new drug. This course will present the Bayesian adaptive approach to the design and analysis of clinical trials. We will ...
... A clinical trial is a research study conducted to assess the utility of an intervention in volunteers and, in general, it provides the evidence to support regulatory approval of a new drug. This course will present the Bayesian adaptive approach to the design and analysis of clinical trials. We will ...
Class 4. Leverage, residuals and influence
... The studentized residuals are driven by the leave one out idea, which is the basis for much computationally intensive modern statistics. The leave one out idea is often called “jackknifing”. This “leave one out” residual can be used as a basis for judging the predictive ability of a model. Clearly t ...
... The studentized residuals are driven by the leave one out idea, which is the basis for much computationally intensive modern statistics. The leave one out idea is often called “jackknifing”. This “leave one out” residual can be used as a basis for judging the predictive ability of a model. Clearly t ...
Slide 1 - Carnegie Mellon University
... •Different types of relations (links) •Attributes may be correlated •Examples: – actors, directors, movies, companies – papers, authors, conferences, citations – company, employee, customer, ...
... •Different types of relations (links) •Attributes may be correlated •Examples: – actors, directors, movies, companies – papers, authors, conferences, citations – company, employee, customer, ...
Predicting the Demand for Frequently Purchased Items
... purchase rates of a range of items including durables, services, and fast moving consumer goods, over time periods from three months to a year (Day, Gan, Gendall & Esslemont 1991). In all these cases the Juster scale has proved a better predictor than purchase intention scales. However, for frequent ...
... purchase rates of a range of items including durables, services, and fast moving consumer goods, over time periods from three months to a year (Day, Gan, Gendall & Esslemont 1991). In all these cases the Juster scale has proved a better predictor than purchase intention scales. However, for frequent ...
Business Intelligence and Insurance
... exhibit common characteristics, in different segments. These segments can then be treated as distinct entities and the future interaction with them can be tailored accordingly. Customer segmentation can save a lot of marketing effort, which would otherwise go waste. Often data mining tools are used ...
... exhibit common characteristics, in different segments. These segments can then be treated as distinct entities and the future interaction with them can be tailored accordingly. Customer segmentation can save a lot of marketing effort, which would otherwise go waste. Often data mining tools are used ...
Self-BLAME
... BUT… • It doesn’t look like gender is having much of an effect • Check SPSS output and see that Wald χ2 for Gender is 0.527, which has p = .47 • Perhaps it wasn’t worth adding both parameters, but it will be worth just adding Age • Age has Wald-χ2 = 4.33, p = .03 • When we only add Age, change in χ ...
... BUT… • It doesn’t look like gender is having much of an effect • Check SPSS output and see that Wald χ2 for Gender is 0.527, which has p = .47 • Perhaps it wasn’t worth adding both parameters, but it will be worth just adding Age • Age has Wald-χ2 = 4.33, p = .03 • When we only add Age, change in χ ...
Subject CT4 – Models Institute of Actuaries of India
... Describe the process of sensitivity testing of assumptions and explain why this forms an important part of the modelling process. ...
... Describe the process of sensitivity testing of assumptions and explain why this forms an important part of the modelling process. ...
Identifying and Overcoming Common Data Mining Mistakes
... one nontrivial level. If only one dominant level appears, the variable is highly likely to be useless in any model since a large portion of the observations cannot be differentiated with respect to this variable. However, in the case of modeling rare events, it is still possible that an infrequently ...
... one nontrivial level. If only one dominant level appears, the variable is highly likely to be useless in any model since a large portion of the observations cannot be differentiated with respect to this variable. However, in the case of modeling rare events, it is still possible that an infrequently ...
Abstract
... presented. The strategy enables discovery of deviations from the presumed load distributions and is applied to increase CLUS accuracy. A novel model-based collaborative filtering approach that utilizes linear regression, an unsupervised machine learning technique, is presented. ADVANTAGES OF PROPO ...
... presented. The strategy enables discovery of deviations from the presumed load distributions and is applied to increase CLUS accuracy. A novel model-based collaborative filtering approach that utilizes linear regression, an unsupervised machine learning technique, is presented. ADVANTAGES OF PROPO ...
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Data Modeling [Comparison of data modeling techniques ]
... UML is an object modeling technique It models object classes instead of entities In the object oriented world the relationships are called as associations Cardinality and optionality in UML is conveyed by characters or numbers Express in the form of more complex upper and lower limits UML ...
... UML is an object modeling technique It models object classes instead of entities In the object oriented world the relationships are called as associations Cardinality and optionality in UML is conveyed by characters or numbers Express in the form of more complex upper and lower limits UML ...
Magic Quadrant for Customer Data-Mining Applications
... aspects of the relationship, such as Web traffic, and more granularity of data, such as item rather than category tracking of customer purchases).This growth in data feeds enables a growth in demand for the ability to analyze the data and deploy the resulting analyses into business processes. This d ...
... aspects of the relationship, such as Web traffic, and more granularity of data, such as item rather than category tracking of customer purchases).This growth in data feeds enables a growth in demand for the ability to analyze the data and deploy the resulting analyses into business processes. This d ...
Symmetry Plus Quasi Uniform Association Model and Its Orthogonal
... when it is s . For example, the odds that the using a head covering for a case in a pair is never instead of frequency is estimated to be 0.426 [= (0.808) 4 ] times higher when that for control in the pair is occasionally than when it is ...
... when it is s . For example, the odds that the using a head covering for a case in a pair is never instead of frequency is estimated to be 0.426 [= (0.808) 4 ] times higher when that for control in the pair is occasionally than when it is ...