Examples of using Input variables in English and their translations into Indonesian
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Colloquial
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Ecclesiastic
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Computer
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Ecclesiastic
These become the Input Variables within the Expert.
Those columns that are the inputs are referred to as input variables.
Where A and B are input variables, X is an output variable. .
Input variables used in this study is the operational cost, total assets and labor costs.
In Monte Carlo simulation,it is possible to form independent relationships between input variables.
The blue numbers are input variables and you can change them if you would like to adjust the model.
In Monte Carlo simulation,it's possible to model interdependent relationships between input variables.
These are generic functions that use input variables to tailor the results of the function to a particular bond.
This technique isused within specific boundaries that depend on one or more input variables.
The order of tasks to using this tool starts with identifying the input variables and the response(output) that is to be measured.
In Monte Carlo simulation,it is not impossible to model interdependent connections between input variables.
Each gate has one or two binary input variables designated by A and B and one binary output variable designated by x.
The output of the decoder are nothing but the min terms of‘n‘ input variables(lines), when it is enabled.
The original Black-Scholes model required five input variables- strike price of an option, current price of the stock, time to expiration, risk-free rate, and volatility.
This method is used within some boundaries which depends on one or more input variables.
User-Defined Input Variables: It is up to each trader to decide which technical indicators to use, as well as to determine how best to use the indicators.
In Monte Carlo simulation,it is possible to form independent relationships between input variables.
Thus an algorithm can be an algebraic equation such as y m+ n-two arbitrary"input variables" m and n that produce an output y.
This technique isused within specific boundaries that depend on one or more input variables.
This DOE approach plans for all possible dependencies and prescribes exactly what datasets are required for assessment i.e. whether input variables change the response on their own, when combined, or not at all.
In Monte Carlo simulation,it's possible to model interdependent relationships between input variables.
DOE plans for all possible dependencies in the first place, andthen prescribes exactly what data are needed to assess them i.e. whether input variables change the response on their own, when combined, or not at all.
These 16 functions are enumerated below,together with their outputs for each combination of input variables.
Thus we might expect an algorithm to be an algebraic equation such as y= m+ n-two arbitrary“input variables” m and n that produce an output y.
The purpose is to determine the class of an observationbased on a set of variables known as predictors or input variables.
Simply defined,algorithms follow a series of instructions to solve a problem based on the input variables in the underlying model.