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ISYE 6501 Midterm Questions with 100% correct answers | verified | latest update 2024
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ISYE 6501 MidtermWhat does SVM stand for? - ANS-Support Vector Machine
Is written text structured or unstructured? - ANS-Unstructured
When we increase the sum of the square of the coefficients we... - ANS-Decrease the
distance between the lines
In SVM soft classifier we tradeoff between maximizing ___ and minimizing ___ -
ANS-margin and errors
If lambda gets small what gets emphasized, large margin or minimizing training error?, -
ANS-Minimizing errors.
What is a support vector? - ANS-A point that holds up a shape.
Does ...[⅔(a-1)+1/3(a+1)] move an SVM classifier up or down? - ANS-Up
How do you make errors more costly in a soft SVM classifier? - ANS-include a multiplier
for the point-error term.
If an SVM coefficient is very close to zero... - ANS-that term is not very important to the
classification.
What is the difference between standardization and scaling? - ANS-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? - ANS-Euclidean distance
What is the 1-norm? - ANS-The rectilinear (Manhattan) distance
What is the infinity norm? - ANS-The value of the largest dimension
Measuring the quality of a model is called? - ANS-Validation
What does a confusion matrix show? - ANS-The performance of a classification model.
,A time series outlier that seems "off the curve" is called a... - ANS-contextual outlier.
A data element that is different from all other data in a set is called a... - ANS-point
outlier.
When something is missing in a range of points - ANS-it is called a..., collective outlier.
The whiskers on a box plot extend to... - ANS-the 10th and 90th percentiles (or 5th and
95th)
Why are hypothesis tests generally not sufficient for change detection? - ANS-They are
slow to detect changes.
In CUSUM, T is _____ and C is _____., - ANS-Threshold and a "bring down factor"
In a CUSUM model, you adjust T and C to manage the tradeoff between..., - ANS-early
detection and false-alarms
In exponential smoothing, if the data is less random, then you want to pick an alpha that
is..., - ANS-Close to 1.
What is the initial condition for T in exponential smoothing with trending? - ANS-T_i=0
In cyclic exponential smoothing, L represents..., - ANS-The length of the cycle or
season
In cyclic exponential smoothing, C_1 ... C_L = ___?, - ANS-1. In other words, initialize it
to no initial cycle.
Exponential, trending and cyclic smoothing are also referred to as - ANS-single double
and triple.
Triple smoothing is also known as? - ANS-Winter's or Holt-Winter's
What is the optimization formula for Exponential Smoothing? - ANS-min(F_t-Xt)^2
where alpha and beta are between 0 and 1.
ARIMA stands for? - ANS-Autoregressive Integrated Moving Average
, Exponential smoothing is an order ___ autoregressive model. - ANS-Infinity. It uses
data going all the way back.
For ARIMA, the D parameter is used to specify ___. - ANS-, The order, or the
differences of the differences of the differences (d-times.)
For ARIMA, the P parameters is used to specify ____., - ANS-The order of periods
(autoregression).
For ARIMA, the Q parameter is used to specify ______., - ANS-The order of the moving
average.
ARIMA(0,1,1) is ?, - ANS-Exponential smoothing.
What is the order of the ARIMA parameters? - ANS-p d q
GARCH estimates what? - ANS-Variance.
Variance can be a proxy for ___ or ___. - ANS-volatility or Risk
What parameter does GARCH not have the ARIMA has? - ANS-d because GARCH
doesn't deal with differences.
What is a simple linear regression? - ANS-Linear regression with one predictor.
A linear regression defines a relationship between what and what? - ANS-Predictor(S)
and Response
What is the formula for a linear regression with M predictors? - ANS-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? -
ANS-Square of the difference between the line and the data points. (Sum squared
error.)
What is the formula for point error in linear regression? - ANS-y(i)-Yhat(i)=y(i)-(a(0) +
a(i)*x(i)
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