ISYE6501: MIDTERM 1flashcards
Matching models/methods to categories
(cusum and pca = NONE)
Select all of the following models that are designed for use with attribute/feature data (i.e., not
time-series data):
k-nearest-neighbor, PCA, k-means, logistic regression, linear regression, random forest, SVM's
Brainpower
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0:15
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Classification models
CART, k-nearest-neighbor, logistic regression, random forest, support vector machine
Clustering
k-means
Response prediction
ARIMA, Exponential smoothing, Linear regression
Validation
cross-validation
Matching models/methods to categories
(cusum and pca = NONE)
Select all of the following models that are designed for use with attribute/feature data (i.e., not
time-series data):
k-nearest-neighbor, PCA, k-means, logistic regression, linear regression, random forest, SVM's
Brainpower
Read More
Previous
Play
Next
Rewind 10 seconds
Move forward 10 seconds
Unmute
0:02
/
0:15
Full screen
Classification models
CART, k-nearest-neighbor, logistic regression, random forest, support vector machine
Clustering
k-means
Response prediction
ARIMA, Exponential smoothing, Linear regression
Validation
cross-validation
