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DSE1101 > Formula for DSE part 2 > Flashcards

Formula for DSE part 2 Flashcards

1
Q

What is N, P and yi

A
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2
Q

What is the formula for forecast or predictive distribution?

A

F(y) = P(Y ≤ y).

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3
Q

What is the formula for forecast error?

A
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4
Q

What is the formula for quadratic and absolute loss function?

A
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5
Q

What is the general formula of risk

A
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6
Q

What is the general formula of risk for quadratic and absolut eloss

A
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7
Q

What is the formula for (Conditional) predictive modeling?

A
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8
Q

What is the formula for optimal conditional point forecast?

A
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9
Q

What is the formula for optimal conditional point forecast for quadratic loss?

A
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10
Q

What is the formula for the common loss function

A

“0-1” loss

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11
Q

What is euclidean distance formula?

A
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12
Q

What are the steps for knn?

What is the formula for conditional probabilities?

A
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13
Q

What is the formula for standardize and scaling?

A
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14
Q

What is the formula for the last step of knn? for regression task

A
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15
Q

What is the formula for in sample and out sample MSE for KNN?

A
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16
Q

What is the general formula for mean squared error for forecast for knn?

A
17
Q

What is bayes rule?

A
18
Q

What is the formula for likelihood? (slide 4)

A
19
Q

What is the formula for prior probability and evidence? (slkide 4)

A
20
Q

What is formula for Bayes theorem for a mix of discrete and continuous X and discrete Y(SLIDE 7)

A

kind of like joint density

21
Q

What is the formula for the naive bayes classifier? (slide 11)

A

still need to estimate the marginal densities ƒ𝑘j

22
Q

What is the formula for the average of outcomes falling into rectangle for decision tree? (slide 7)

A
23
Q

What do you want to minimise in regression tree? (slide 7)

A

W

24
Q

What are the steps to building decision trees? (slide 9)

A
25
Q

What is the minimisation problem for tree choice in decision trees? (slide 23)

A
26
Q

What is the formula for L(T,y) (slide 34). Explain what are the variable names

A

m indexes terminal nodes in tree T.
Nm is the no of obs. in terminal node m.
ym is the vector of outcomes for obs. in terminal node m.

27
Q

What is the formula for pmk hat? (slide 34)

A
28
Q

What is the formula for misclassification error generally and for binary case(slide 35)

A
29
Q

What is the formula for gini index generally and for binary case(slide 35)

A
29
Q

What is the formula for cross entropy or deviance generally and for binary case(slide 35)

A
30
Q

What does the k means clustering minimise?

A
31
Q

What does the first term represent in information criteria?

A
32
Q

What is the formula for Zm

A
33
Q

What is level, twist,butterfly movements?

A

draw them out

34
Q

What is the formula for the linear regression model fitted?

A

slide 30

35
Q
A

DSE1101 (12 decks)

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