ISYE 6501 MIDTERM QUESTIONS WITH ANSWERS VERIFIED BY EXPERTS 2024 NEW UPDATED
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ISYE 6501
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ISYE 6501
ISYE 6501 MIDTERM QUESTIONS WITH
ANSWERS VERIFIED BY EXPERTS 2024 NEW UPDATED
ISYE 6501 MIDTERM QUESTIONS WITH
ANSWERS VERIFIED BY EXPERTS 2024 NEW UPDATED
ISYE 6501 MIDTERM QUESTIONS WITH
ANSWERS VERIFIED BY EXPERTS 2024 NEW UPDATED
ISYE 6501 MIDTERM QUESTIONS WITH
ANSWERS VERIFIED BY E...
ISYE 6501 MIDTERM QUESTIONS WITH
ANSWERS VERIFIED BY EXPERTS
2024 NEW UPDATED
What measure is used to determine the quality of a linear regression line to data? -
CORRECT ANSWER>>>>Square of the difference between the line and the data
points. (Sum squared error.)
What is the formula for point error in linear regression? - CORRECT ANSWER>>>>y(i)-
Yhat(i)=y(i)-(a(0) + a(i)*x(i)
Taking partial derivates and setting them equal to zero and then solving that system
equation helps us do what? - CORRECT ANSWER>>>>Minimize the error and optimize
the coefficients for linear regression.
What does AIC stand for? - CORRECT ANSWER>>>>Akaike Information Criterion
What is "Likelihood"? - CORRECT ANSWER>>>>A measure for the probability density
for any parameter set.
What is Maximum likelihood? - CORRECT ANSWER>>>>Parameters that give the
highest probability.
What is MLE? - CORRECT ANSWER>>>>Maximum Likelihood Estimate... The set of
parameters that minimizes the sum of square errors.
What is the formula for AIC? - CORRECT ANSWER>>>>AIC=2k - 2*ln(L*) where L* is
the maximum likelihood value and K is the number of parameters estimated.
What is the penality term in AIC and what does it do? - CORRECT ANSWER>>>>2K -
It helps prevent overfitting.
A models that is fit to random effects and not real ones is said to be? - CORRECT
ANSWER>>>>Overfit
What does corrected AIC account for? - CORRECT ANSWER>>>>The fact that we
cannot have infinitely many data points.
,If AIC for model 1 is 75 and AIC for model 2 is 80 how do you compute which is better. -
CORRECT ANSWER>>>>It is the relative likelyhood: e^((AIC1-AIC2)/2) = 8.2%
What does BIC stand for? - CORRECT ANSWER>>>>Bayesian Information Criterion
If you have a lot more data than parameters should you use AIC or BIC? - CORRECT
ANSWER>>>>BIC
If you have "fewer" parameters - CORRECT ANSWER>>>>should you use AIC or
BIC?, BIC
The "Rule of Thumb" deals with? - CORRECT ANSWER>>>>When comparing two
models on the same data set by their BIC scores.
In exponential smoothing what does alpha do? - CORRECT ANSWER>>>>Adjust the
trade off between current (x_t) and previous values.
In exponential how should you adjust for randomness? - CORRECT
ANSWER>>>>Make alpha close to 0.
In exponential trending, what does Beta do? - CORRECT ANSWER>>>>Adjusts for
trending.
In exponential smoothing, what is C_t? - CORRECT ANSWER>>>>A multiplicative
seasonality factor at time t.
In exponential smoothing, what is L? - CORRECT ANSWER>>>>The length of a cycle.
In exponential smoothing, what does gamma do? - CORRECT ANSWER>>>>Adjusts
how much cycles contribute to the model.
In multiplicative seasonality, the first L values of C are set to what? - CORRECT
ANSWER>>>>1.
1-norm - CORRECT ANSWER>>>>Similar to rectilinear distance; measures the sum of
the lengths of each dimension
2-norm - CORRECT ANSWER>>>>Similar to Euclidian distance; measures the
straight-line length of a vector from the origin.
Additive seasonality - CORRECT ANSWER>>>>Seasonal effect that is added to a
baseline value.
, Adjusted R-squared/Adjusted R2 - CORRECT ANSWER>>>>Variant of R2 that
encourages simpler models by penalizing the use oftoo many variables.
AIC - CORRECT ANSWER>>>>Akaike information criterion
Akaike information criterion - CORRECT ANSWER>>>>Model selection technique that
trades off between model fit and model complexity. Model with lower AIC is preferred.
Generally penalizes complexity less than BIC.
Algorithm - CORRECT ANSWER>>>>Step-by-step procedure designed to carry out a
task.
Analysis of Variance/ANOVA - CORRECT ANSWER>>>>Statistical method for dividing
the variation in observations among different sources.
Area under curve/AUC - CORRECT ANSWER>>>>Area under the ROC curve; an
estimate of the classification model's accuracy. Also called concordance index.
Attribute - CORRECT ANSWER>>>>A characteristic or measurement - for example, a
person's height or the color of a car. Aka "feature", "covariate" or "predictor"
Autoregression - CORRECT ANSWER>>>>Regression technique using past values of
time series data as predictors of future values.
Autoregressive integrated moving average (ARIMA) - CORRECT ANSWER>>>>Time
series model that uses differences between observations when data is nonstationary.
Also called Box-Jenkins.
Bayesian Information criterion - CORRECT ANSWER>>>>(BIC) Model selection
technique that trades off model fit and model complexity. Generally penalizes
complexity more than AIC. Lower is better.
Bayesian regression - CORRECT ANSWER>>>>Regression model that incorporates
estimates of how coefficients and error are distributed.
BIC - CORRECT ANSWER>>>>Bayesian information criterion
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