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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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