Four-class labels
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|---|---|---|---|---|
1 | 0 |
logistic regression
|
analyzes relationships between a nominal level dependent variable and more than two independent variables yields an odds ratio
|
a multivariate regression procedure that analyzes relationships between one or more independent variables and a categorical dependent variable.
|
3 | 1 |
logistic regression
|
outputs a value that corresponds to the probability of belonging to a class, used for classification
|
a method of classification: the model outputs the probability of a categorical target variable y belonging to a certain class.
|
1 | 0 |
logistic regression
|
allows prediction of a discrete outcome from a set of variables that may be discrete, continuous, dichotomous or a combo
|
shows correlation and does not establish causation between independent predictor variable and dependent categorical variables
|
0 | 0 |
logistic regression
|
the outcome (dependent variable) has only a limited number of possible values... used when the response variable is of a categorical nature.
|
model where the dependent variable is categorical. estimates the probability of a relationship between a categorical variable and one or more independent variables
|
0 | 0 |
logistic regression
|
models the probability that y belongs to a particular category. always produces an s-shaped curve.
|
a type of generalized linear model in which the predicted values are probabilities
|
1 | 0 |
logistic regression
|
compares two groups or predictor variables dv=binary (yes/no) while controlling for confounding variables
|
predict the probability that an event will occur (categorical variables) predicting students acceptance based on gpa above 3.0 and act above 25
|
0 | 0 |
logistic regression
|
pairwise regression. logistic probability unit (logit) is computed of the ratio of the probability of class a over class b. minimize the mean square error. maximize log-likelihood
|
a type of generalized linear model in which the predicted values are probabilities
|
1 | 0 |
logistic regression
|
outputs a value that corresponds to the probability of belonging to a class, used for classification
|
a type of generalized linear model in which the predicted values are probabilities
|
0 | 0 |
logistic regression
|
logistic regression is a statistical method for analyzing a data set in which there are one or more independent variables that determine an outcome y is qualitative
|
used when you want to use predictor variables but you don't have a discrete criterion variable; allows you to identify factors
|
1 | 0 |
logistic regression
|
extends the ideas of linear regression to the situation where the dependent variable, y, is categorical. we can think of a categorical variable as dividing the observations into classes.
|
an algebraic function that is used to relate any and all independent variables to the expected dependent variable.
|
1 | 0 |
logistic regression
|
is a widely used statistical model that, in its basic form, uses a logistic function to model a binary dependent variable; many more complex extensions exist.
|
can be used to model the association bt 2 or more independent varibels and one dependent
|
1 | 0 |
logistic regression
|
approach that assigns a label to new data based on the odds that the data belongs to a certain category
|
use to estimate the probability that a sample belongs to a particular class
|
3 | 1 |
logistic regression
|
- a classification algorithm to assign observations to a discrete set of classes : (cat, dog, horse). - generally, returns the probability of each class being the
|
approach that assigns a label to new data based on the odds that the data belongs to a certain category
|
0 | 0 |
logistic regression
|
pairwise regression. logistic probability unit (logit) is computed of the ratio of the probability of class a over class b. minimize the mean square error. maximize log-likelihood
|
-coeffs are estimated using a technique called maximum likelihood estimation
|
1 | 0 |
logistic regression
|
models the probability that y belongs to a particular category. always produces an s-shaped curve.
|
-coeffs are estimated using a technique called maximum likelihood estimation
|
0 | 0 |
logistic regression
|
1) binary or categorical variable 2) independent observations 3) chi-square test assumes sufficient numbers in each cell (>=5)
|
predict probability of a categorical variable predict if something is true or false instead of a continuous measurement fit data into and s-curve logistic function
|
1 | 0 |
logistic regression
|
extends the ideas of linear regression to the situation where the dependent variable, y, is categorical. we can think of a categorical variable as dividing the observations into classes.
|
predict probability of a categorical variable predict if something is true or false instead of a continuous measurement fit data into and s-curve logistic function
|
1 | 0 |
logistic regression
|
models the probability that y belongs to a particular category. always produces an s-shaped curve.
|
outputs a value that corresponds to the probability of belonging to a class, used for classification
|
1 | 0 |
logistic regression
|
a type of generalized linear model in which the predicted values are probabilities
|
a method of classification: the model outputs the probability of a categorical target variable y belonging to a certain class.
|
0 | 0 |
logistic regression
|
1 dependent variable (binary categorical variable), 2+ independent variable(s) (continuous or discrete variables)
|
a nonlinear regression model that relates a set of explanatory variables to a dichotomous dependent variable. output is a probability estimate for binary variable.
|
1 | 0 |
logistic regression
|
logistic regression is a probabilistic statistical regression model which is used to model the relationship between predictor variables and categorical response or dependent variables
|
a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables.
|
0 | 0 |
logistic regression
|
the outcome (dependent variable) has only a limited number of possible values... used when the response variable is of a categorical nature.
|
an algebraic function that is used to relate any and all independent variables to the expected dependent variable.
|
3 | 1 |
logistic regression
|
a probabilistic regression model which is used to model the relationship between predictor variables and categorical response or dependent variables.
|
a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables.
|
0 | 0 |
logistic regression
|
pairwise regression. logistic probability unit (logit) is computed of the ratio of the probability of class a over class b. minimize the mean square error. maximize log-likelihood
|
models the probability that y belongs to a particular category. always produces an s-shaped curve.
|
1 | 0 |
logistic regression
|
estimates a probability that the outcome variable assumes a certain value
|
logistic regression is a statistical method for analyzing a data set in which there are one or more independent variables that determine an outcome y is qualitative
|
0 | 0 |
logistic regression
|
model where the dependent variable is categorical. estimates the probability of a relationship between a categorical variable and one or more independent variables
|
extends the ideas of linear regression to the situation where the dependent variable, y, is categorical. we can think of a categorical variable as dividing the observations into classes.
|
0 | 0 |
logistic regression
|
model where the dependent variable is categorical. estimates the probability of a relationship between a categorical variable and one or more independent variables
|
an algebraic function that is used to relate any and all independent variables to the expected dependent variable.
|
0 | 0 |
logistic regression
|
model where the dependent variable is categorical. estimates the probability of a relationship between a categorical variable and one or more independent variables
|
1) binary or categorical variable 2) independent observations 3) chi-square test assumes sufficient numbers in each cell (>=5)
|
0 | 0 |
logistic regression
|
the outcome (dependent variable) has only a limited number of possible values... used when the response variable is of a categorical nature.
|
shows correlation and does not establish causation between independent predictor variable and dependent categorical variables
|
0 | 0 |
logistic regression
|
statistical model used to study the relationship between independent and dependent variables when the dependent variable consists of binomial data.
|
predicting an outcome variable from multiple independent variables where the outcome variable is nominal, and the independent variables are nominal, interval, or ratio
|
2 | 1 |
logistic regression
|
logistic regression is a probabilistic statistical regression model which is used to model the relationship between predictor variables and categorical response or dependent variables
|
a probabilistic regression model which is used to model the relationship between predictor variables and categorical response or dependent variables.
|
3 | 1 |
logistic regression
|
- a classification algorithm to assign observations to a discrete set of classes : (cat, dog, horse). - generally, returns the probability of each class being the
|
use to estimate the probability that a sample belongs to a particular class
|
3 | 1 |
logistic regression
|
predicts the probability of a particular level of the target variable at the given value of the input variable linear classification binary variables
|
binary dependent variable - predicts the probability of a particular level of the target variable at the given value of the input variable
|
0 | 0 |
logistic regression
|
pairwise regression. logistic probability unit (logit) is computed of the ratio of the probability of class a over class b. minimize the mean square error. maximize log-likelihood
|
a method of classification: the model outputs the probability of a categorical target variable y belonging to a certain class.
|
0 | 0 |
logistic regression
|
1) binary or categorical variable 2) independent observations 3) chi-square test assumes sufficient numbers in each cell (>=5)
|
shows correlation and does not establish causation between independent predictor variable and dependent categorical variables
|
3 | 1 |
logistic regression
|
a nonlinear regression model that relates a set of explanatory variables to a dichotomous dependent variable (binary).
|
a nonlinear regression model that relates a set of explanatory variables to a dichotomous dependent variable. output is a probability estimate for binary variable.
|
0 | 0 |
logistic regression
|
predict probability of a categorical variable predict if something is true or false instead of a continuous measurement fit data into and s-curve logistic function
|
shows correlation and does not establish causation between independent predictor variable and dependent categorical variables
|
0 | 0 |
type system
|
common type system used to identify the data types you can use in a program
|
a set of types and the rules that govern their use in programs
|
0 | 0 |
type system
|
defines how a programming language classifies values and expressions into types, how it can manipulate those types and how they interact
|
a tractable syntactic method for proving the absence of certain program behaviours by classifying (program) phrases according to the kinds of values they compute
|
1 | 0 |
type system
|
common type system used to identify the data types you can use in a program
|
the set of rules for how objects can be used according to their types
|
3 | 1 |
type system
|
the set of rules for how objects can be used according to their types
|
a set of types and the rules that govern their use in programs
|
1 | 0 |
personal information
|
includes information that is classified or privileged
|
information that can personally identify someone, such as their name, email address or billing information, or other data which can be reasonably linked to such information.
|
0 | 0 |
personal information
|
any information from which the identity of an individual is apparent
|
includes information that is classified or privileged
|
0 | 0 |
personal information
|
includes information that is classified or privileged
|
- information that can certainly identify an individual
|
3 | 1 |
personal information
|
information that can personally identify someone, such as their name, email address or billing information, or other data which can be reasonably linked to such information.
|
- information that can certainly identify an individual
|
3 | 1 |
personal information
|
any information from which the identity of an individual is apparent
|
- information that can certainly identify an individual
|
2 | 1 |
personal information
|
information that can be used to identify you, such as your age, gender, how many brothers and sisters you have, your favorite food, address, telephone number, school, etc.
|
information that can't be used to identify you (example: your age, gender, how many siblings you have, favorite food, etc.)
|
2 | 1 |
personal information
|
any information from which the identity of an individual is apparent
|
information that can personally identify someone, such as their name, email address or billing information, or other data which can be reasonably linked to such information.
|
0 | 0 |
total cost
|
includes the expected and unexpected elements that increase the unit cost of a good, service, or piece of equipment
|
the path cost plus the search cost which is the time complexity but can including the space somplexity.
|
1 | 0 |
total cost
|
the sum of the fixed cost and variable cost at each level of output
|
because some costs can not be changed in the short run, total production costs are separated into fixed and variable costs
|
2 | 1 |
total cost
|
because some costs can not be changed in the short run, total production costs are separated into fixed and variable costs
|
the cost of all the inputs used by a firm, or fixed costs plus variable costs (tc=fc+vc)
|
1 | 0 |
total cost
|
the amount that the firm pays to buy inputs the market value of the inputs a firm uses in production
|
the market value of the inputs a firm uses in production -sum of fixed and variable costs
|
2 | 1 |
exhaustive search
|
a search that continues until the test item is compared with all items in the memory set
|
a search for information in which each item in a set is examined, even after the target is found.
|
3 | 1 |
exhaustive search
|
a search of memory that continues to examine the remaining items in memory even after the target item has been found; contrasts with self-terminating search
|
one the continues to examine the remaining items in memory even after target is found
|
1 | 0 |
exhaustive search
|
assuming n features examine all (n d) subsets of size d select subset that performs best according to criterion function
|
goal: find parsimonious model (the simplest model that performs sufficiently well), higher predictive accuracy and more robust; all possible subsets of predictors assessed, computationally intensive, judged by &"adjusted r-squared&"
|
3 | 1 |
exhaustive search
|
a search of memory that continues to examine the remaining items in memory even after the target item has been found; contrasts with self-terminating search
|
a search for information in which each item in a set is examined, even after the target is found.
|
3 | 1 |
exhaustive search
|
a search that continues until the test item is compared with all items in the memory set
|
one the continues to examine the remaining items in memory even after target is found
|
2 | 1 |
exhaustive search
|
one the continues to examine the remaining items in memory even after target is found
|
a search for information in which each item in a set is examined, even after the target is found.
|
3 | 1 |
binary data
|
type of nominal variable that has only 2 possible values - ie gender, yes/no
|
data that can take only two different values (true/false, 0/1, black/white, on/off, etc.).
|
3 | 1 |
binary data
|
data that can take only two different values (true/false, 0/1, black/white, on/off, etc.).
|
categorical data that have two possible values -i.e. are yes/no or success/failure.
|
3 | 1 |
binary data
|
type of nominal variable that has only 2 possible values - ie gender, yes/no
|
categorical data that have two possible values -i.e. are yes/no or success/failure.
|
2 | 1 |
binary data
|
data is &"either/or&" or &"yes/no&". there are only two possible outcomes
|
data that can take only two different values (true/false, 0/1, black/white, on/off, etc.).
|
3 | 1 |
binary data
|
type of nominal variable that has only 2 possible values - ie gender, yes/no
|
data is &"either/or&" or &"yes/no&". there are only two possible outcomes
|
0 | 0 |
binary data
|
have few observations per covariate pattern. usually has more continuous variables in the model.
|
because the expected value must be between zero and one, link functions that force that to happen should be used. the logistic function is the most common choice.
|
3 | 1 |
binary data
|
data is &"either/or&" or &"yes/no&". there are only two possible outcomes
|
categorical data that have two possible values -i.e. are yes/no or success/failure.
|
0 | 0 |
holistic approach
|
linked with other scientific and social disciplines (geology, physics, law, economics etc.)
|
you cannot understand human beings without understanding the full range of the human phenomenon
|
1 | 0 |
holistic approach
|
you cannot understand human beings without understanding the full range of the human phenomenon
|
within traditional medicine, a manner of understanding health such that it encompasses all aspects - physical, mental, social, and spiritual - of a person's life.
|
2 | 1 |
knowledge management
|
a process that helps manipulate important knowledge that comprises part of the organisations memory, usually in an unstructured format
|
a process that helps organizations manipulate important knowledge that comprises part of the organization's knowledge/intellectual capital
|
1 | 0 |
knowledge management
|
doing what is needed to get the most out of knowledge resources. focuses on creating, sharing, and applying knowledge.
|
the way an organization identifies and leverages knowledge to be competitive -act of creating value by using intellectual capital
|
1 | 0 |
knowledge management
|
responsible for creating and managing useful knowledge and making it available to authorized individuals who will use it to enhance organizational performance.
|
the process of creating, identifying, collecting, organizing, sharing, and using knowledge and knowledge sources for the benefit of the organization or business
|
1 | 0 |
knowledge management
|
maintaining a fact base about the organization; including benchmarks, and work processes and making these facts available to associates
|
business processes developed for creating, storing, transferring, and applying knowledge; can be a major source of profit and competitive advantage
|
0 | 0 |
knowledge management
|
a type of it-enabled organizational relationship that has important implications for both organizational learning and decision making.
|
focuses on processes designed to improve an organization's ability to capture, share and use tacit knowledge in a manner that will improve performance
|
2 | 1 |
knowledge management
|
- knowledge creation - knowledge dissemination - knowledge application & integration - sources of competitive advantage
|
doing what is needed to get the most out of knowledge resources. focuses on creating, sharing, and applying knowledge.
|
3 | 1 |
knowledge management
|
managing tacit and explicit knowledge for reusing existing knowledge and creating new knowledge
|
this is aimed at both explicit and tacit types for two purposes: - reusing knowledge that already exists - creating new knowledge
|
1 | 0 |
knowledge management
|
any structured activity that improves an organizations capacity to acquire, share, and use knowledge in ways that improve it's survival and success
|
the way an organization identifies and leverages knowledge to be competitive -act of creating value by using intellectual capital
|
1 | 0 |
knowledge management
|
doing what is needed to get the most out of knowledge resources. focuses on creating, sharing, and applying knowledge.
|
the process of identifying, capturing, organizing, & using knowledge assets to create + sustain competitive advantage
|
1 | 0 |
knowledge management
|
the process of creating, identifying, collecting, organizing, sharing, and using knowledge and knowledge sources for the benefit of the organization or business
|
maintaining a fact base about the organization; including benchmarks, and work processes and making these facts available to associates
|
0 | 0 |
knowledge management
|
any structured activity that improves an organizations capacity to acquire, share, and use knowledge in ways that improve it's survival and success
|
the process of identifying, capturing, organizing, & using knowledge assets to create + sustain competitive advantage
|
0 | 0 |
knowledge management
|
- knowledge creation - knowledge dissemination - knowledge application & integration - sources of competitive advantage
|
its purpose is to translate the hco's complete knowledge resource to improvement of its strategic performance
|
2 | 1 |
knowledge management
|
this system creates the process of sharing knowledge among people for the benefit of the business.
|
collaboration and sharing of information among employees or customers
|
1 | 0 |
knowledge management
|
a process that helps organizations manipulate important knowledge that comprises part of the organization's knowledge/intellectual capital
|
the process of creating an inclusive, comprehensive, easily accessible organizational memory, which is often called the organization's intellectual capital.
|
1 | 0 |
knowledge management
|
the process of creating an inclusive, comprehensive, easily accessible organizational memory, which is often called the organization's intellectual capital.
|
process that helps organizations manipulate important knowledge that comprises part of the organization's memory
|
3 | 1 |
knowledge management
|
includes the processes necessary to generate, capture, codify, integrate, and transfer knowledge across the organization to achieve competitive advantage
|
the processes necessary to capture, codify, and transfer knowledge across the organization to achieve competitive advantage
|
2 | 1 |
knowledge management
|
a process that helps manipulate important knowledge that comprises part of the organisations memory, usually in an unstructured format
|
the process of creating an inclusive, comprehensive, easily accessible organizational memory, which is often called the organization's intellectual capital.
|
2 | 1 |
knowledge management
|
the process of identifying, capturing, organizing, & using knowledge assets to create + sustain competitive advantage
|
its purpose is to translate the hco's complete knowledge resource to improvement of its strategic performance
|
3 | 1 |
knowledge management
|
a process that helps manipulate important knowledge that comprises part of the organisations memory, usually in an unstructured format
|
(intellectual capital) is a process that helps organizations manipulate important knowledge that is part of the organizations memory, usually in an unstructured format.
|
3 | 1 |
knowledge management
|
refers to the set of business processes developed in an organization to create, store, transfer, and apply knowledge
|
the set of processes developed in an organization to create, gather, store, maintain, and disseminate the firm's knowledge.
|
1 | 0 |
knowledge management
|
doing what is needed to get the most out of knowledge resources. focuses on creating, sharing, and applying knowledge.
|
its purpose is to translate the hco's complete knowledge resource to improvement of its strategic performance
|
1 | 0 |
knowledge management
|
(intellectual capital) is a process that helps organizations manipulate important knowledge that is part of the organizations memory, usually in an unstructured format.
|
the process of creating an inclusive, comprehensive, easily accessible organizational memory, which is often called the organization's intellectual capital.
|
3 | 1 |
knowledge management
|
is a structured process for the generation,storage,distribution and application of personal experience along with knowledge evidence in organizations
|
structured process for the generation, storage, distribution, and application of both tacit knowledge (personal experience) and explicit knowledge (evidence).
|
1 | 0 |
knowledge management
|
- knowledge creation - knowledge dissemination - knowledge application & integration - sources of competitive advantage
|
the way an organization identifies and leverages knowledge to be competitive -act of creating value by using intellectual capital
|
2 | 1 |
knowledge management
|
(intellectual capital) is a process that helps organizations manipulate important knowledge that is part of the organizations memory, usually in an unstructured format.
|
process that helps organizations manipulate important knowledge that comprises part of the organization's memory
|
2 | 1 |
knowledge management
|
(intellectual capital) is a process that helps organizations manipulate important knowledge that is part of the organizations memory, usually in an unstructured format.
|
a process that helps organizations manipulate important knowledge that comprises part of the organization's knowledge/intellectual capital
|
1 | 0 |
knowledge management
|
a management strategy that promotes an integrated and collaborative approach to the process of information asset creation, capture, organization, access, and use
|
- process of creating, sharing, using and managing of knowledge and information in an organization - collaborative systems is useful
|
2 | 1 |
knowledge management
|
any structured activity that improves an organizations capacity to acquire, share, and use knowledge in ways that improve it's survival and success
|
doing what is needed to get the most out of knowledge resources. focuses on creating, sharing, and applying knowledge.
|
1 | 0 |
knowledge management
|
refers to the process of enhancing company performance by designing and implementing tools, processes, systems, structures, and cultures to improve the creation, sharing, and use of knowledge.
|
tools, processes, systems, structures, etc., to improve the creation, sharing, and use of knowledge
|
3 | 1 |
knowledge management
|
the process of creating, identifying, collecting, organizing, sharing, and using knowledge and knowledge sources for the benefit of the organization or business
|
business processes developed for creating, storing, transferring, and applying knowledge; can be a major source of profit and competitive advantage
|
2 | 1 |
knowledge management
|
responsible for creating and managing useful knowledge and making it available to authorized individuals who will use it to enhance organizational performance.
|
business processes developed for creating, storing, transferring, and applying knowledge.
|
2 | 1 |
linear programming
|
is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships
|
strategy for finding the optimum value - either maximum or minimum - of a linear function that is subject to certain constraints.
|
3 | 1 |
linear programming
|
an optimization strategy; a method to achieve the best outcome of in a mathematical model whose requirements are represented by linear relationships
|
aka linear optimization a technique for achieving the best outcome in a mathematical model whose requirements are represented by linear relationships
|
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