ISYE 6501 Midterm exam study tips 2024 with complete
solution
What does SVM stand for? - ANSWER Support Vector Machine
Is written text structured or unstructured? - ANSWER Unstructured
When we increase the sum of the square of the coefficients we... - ANSWER
Decrease the distance between the lines
In SVM soft classifier we tradeoff between maximizing ___ and minimizing ___ -
ANSWER margin and errors
If lambda gets small what gets emphasized, large margin or minimizing training
error?, - ANSWER Minimizing errors.
What is a support vector? - ANSWER A point that holds up a shape.
Does ...[⅔(a-1)+1/3(a+1)] move an SVM classifier up or down? - ANSWER Up
How do you make errors more costly in a soft SVM classifier? - ANSWER include
a multiplier for the point-error term.
If an SVM coefficient is very close to zero... - ANSWER that term is not very
important to the classification.
What is the difference between standardization and scaling? - ANSWER Scaling is
bounded in range. Standardization is scaling to a normal distribution. Standardization
is the (value - factor mean) / (factor standard deviation)
What is the 2-norm? - ANSWER Euclidean distance
What is the 1-norm? - ANSWER The rectilinear (Manhattan) distance
What is the infinity norm? - ANSWER The value of the largest dimension
Measuring the quality of a model is called? - ANSWER Validation
What does a confusion matrix show? - ANSWER The performance of a
classification model.
A time series outlier that seems "off the curve" is called a... - ANSWER contextual
outlier.
,A data element that is different from all other data in a set is called a... - ANSWER
point outlier.
When something is missing in a range of points - ANSWER it is called a...,
collective outlier.
The whiskers on a box plot extend to... - ANSWER the 10th and 90th percentiles
(or 5th and 95th)
Why are hypothesis tests generally not sufficient for change detection? - ANSWER
They are slow to detect changes.
In CUSUM, T is _____ and C is _____., - ANSWER Threshold and a "bring down
factor"
In a CUSUM model, you adjust T and C to manage the tradeoff between..., -
ANSWER early detection and false-alarms
In exponential smoothing, if the data is less random, then you want to pick an alpha
that is..., - ANSWER Close to 1.
What is the initial condition for T in exponential smoothing with trending? -
ANSWER T_i=0
In cyclic exponential smoothing, L represents..., - ANSWER The length of the cycle
or season
In cyclic exponential smoothing, C_1 ... C_L = ___?, - ANSWER 1. In other words,
initialize it to no initial cycle.
Exponential, trending and cyclic smoothing are also referred to as - ANSWER
single double and triple.
Triple smoothing is also known as? - ANSWER Winter's or Holt-Winter's
What is the optimization formula for Exponential Smoothing? - ANSWER min(F_t-
Xt)^2 where alpha and beta are between 0 and 1.
ARIMA stands for? - ANSWER Autoregressive Integrated Moving Average
Exponential smoothing is an order ___ autoregressive model. - ANSWER Infinity. It
uses data going all the way back.
For ARIMA, the D parameter is used to specify ___. - ANSWER , The order, or the
differences of the differences of the differences (d-times.)
For ARIMA, the P parameters is used to specify ____., - ANSWER The order of
periods (autoregression).
, For ARIMA, the Q parameter is used to specify ______., - ANSWER The order of
the moving average.
ARIMA(0,1,1) is ?, - ANSWER Exponential smoothing.
What is the order of the ARIMA parameters? - ANSWER p d q
GARCH estimates what? - ANSWER Variance.
Variance can be a proxy for ___ or ___. - ANSWER volatility or Risk
What parameter does GARCH not have the ARIMA has? - ANSWER d because
GARCH doesn't deal with differences.
What is a simple linear regression? - ANSWER Linear regression with one
predictor.
A linear regression defines a relationship between what and what? - ANSWER
Predictor(S) and Response
What is the formula for a linear regression with M predictors? - ANSWER
Y=a0+sum(j=1..m, a(j)*(x(j))
What measure is used to determine the quality of a linear regression line to data? -
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? - 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? - ANSWER Minimize the error and optimize the
coefficients for linear regression.
What does AIC stand for? - ANSWER Akaike Information Criterion
What is "Likelihood"? - ANSWER A measure for the probability density for any
parameter set.
What is Maximum likelihood? - ANSWER Parameters that give the highest
probability.
What is MLE? - ANSWER Maximum Likelihood Estimate... The set of parameters
that minimizes the sum of square errors.
What is the formula for AIC? - 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? - ANSWER 2K - It helps
prevent overfitting.
solution
What does SVM stand for? - ANSWER Support Vector Machine
Is written text structured or unstructured? - ANSWER Unstructured
When we increase the sum of the square of the coefficients we... - ANSWER
Decrease the distance between the lines
In SVM soft classifier we tradeoff between maximizing ___ and minimizing ___ -
ANSWER margin and errors
If lambda gets small what gets emphasized, large margin or minimizing training
error?, - ANSWER Minimizing errors.
What is a support vector? - ANSWER A point that holds up a shape.
Does ...[⅔(a-1)+1/3(a+1)] move an SVM classifier up or down? - ANSWER Up
How do you make errors more costly in a soft SVM classifier? - ANSWER include
a multiplier for the point-error term.
If an SVM coefficient is very close to zero... - ANSWER that term is not very
important to the classification.
What is the difference between standardization and scaling? - ANSWER Scaling is
bounded in range. Standardization is scaling to a normal distribution. Standardization
is the (value - factor mean) / (factor standard deviation)
What is the 2-norm? - ANSWER Euclidean distance
What is the 1-norm? - ANSWER The rectilinear (Manhattan) distance
What is the infinity norm? - ANSWER The value of the largest dimension
Measuring the quality of a model is called? - ANSWER Validation
What does a confusion matrix show? - ANSWER The performance of a
classification model.
A time series outlier that seems "off the curve" is called a... - ANSWER contextual
outlier.
,A data element that is different from all other data in a set is called a... - ANSWER
point outlier.
When something is missing in a range of points - ANSWER it is called a...,
collective outlier.
The whiskers on a box plot extend to... - ANSWER the 10th and 90th percentiles
(or 5th and 95th)
Why are hypothesis tests generally not sufficient for change detection? - ANSWER
They are slow to detect changes.
In CUSUM, T is _____ and C is _____., - ANSWER Threshold and a "bring down
factor"
In a CUSUM model, you adjust T and C to manage the tradeoff between..., -
ANSWER early detection and false-alarms
In exponential smoothing, if the data is less random, then you want to pick an alpha
that is..., - ANSWER Close to 1.
What is the initial condition for T in exponential smoothing with trending? -
ANSWER T_i=0
In cyclic exponential smoothing, L represents..., - ANSWER The length of the cycle
or season
In cyclic exponential smoothing, C_1 ... C_L = ___?, - ANSWER 1. In other words,
initialize it to no initial cycle.
Exponential, trending and cyclic smoothing are also referred to as - ANSWER
single double and triple.
Triple smoothing is also known as? - ANSWER Winter's or Holt-Winter's
What is the optimization formula for Exponential Smoothing? - ANSWER min(F_t-
Xt)^2 where alpha and beta are between 0 and 1.
ARIMA stands for? - ANSWER Autoregressive Integrated Moving Average
Exponential smoothing is an order ___ autoregressive model. - ANSWER Infinity. It
uses data going all the way back.
For ARIMA, the D parameter is used to specify ___. - ANSWER , The order, or the
differences of the differences of the differences (d-times.)
For ARIMA, the P parameters is used to specify ____., - ANSWER The order of
periods (autoregression).
, For ARIMA, the Q parameter is used to specify ______., - ANSWER The order of
the moving average.
ARIMA(0,1,1) is ?, - ANSWER Exponential smoothing.
What is the order of the ARIMA parameters? - ANSWER p d q
GARCH estimates what? - ANSWER Variance.
Variance can be a proxy for ___ or ___. - ANSWER volatility or Risk
What parameter does GARCH not have the ARIMA has? - ANSWER d because
GARCH doesn't deal with differences.
What is a simple linear regression? - ANSWER Linear regression with one
predictor.
A linear regression defines a relationship between what and what? - ANSWER
Predictor(S) and Response
What is the formula for a linear regression with M predictors? - ANSWER
Y=a0+sum(j=1..m, a(j)*(x(j))
What measure is used to determine the quality of a linear regression line to data? -
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? - 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? - ANSWER Minimize the error and optimize the
coefficients for linear regression.
What does AIC stand for? - ANSWER Akaike Information Criterion
What is "Likelihood"? - ANSWER A measure for the probability density for any
parameter set.
What is Maximum likelihood? - ANSWER Parameters that give the highest
probability.
What is MLE? - ANSWER Maximum Likelihood Estimate... The set of parameters
that minimizes the sum of square errors.
What is the formula for AIC? - 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? - ANSWER 2K - It helps
prevent overfitting.
