题目内容
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A、Histogram analysis and Binging are both unsupervised methods.
B、Clustering analysis only belongs to top-down split.
C、Interval merging by c2 Analysis can be applied recursively.
D、Decision-tree analysis is Entropy-based discretization.
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A、Min-max normalization
B、Simple scaling
C、Z-score normalization
D、Normalization by decimal scaling
A、Simple random sample without replacement
B、Simple random sample with replacement
C、Stratified sample
D、All above
A、Equal-width (distance) partitioning is the most straightforward, but outliers may dominate presentation.
B、Equal-depth (frequency) partitioning Divides the range into N intervals, each containing approximately same number of samples.
C、The interval of the former one is not equal.
D、The number of tuples is the same when using the latter one.
A、Cross-validation can be used to determine a good value by using an independent dataset to validate the K values.
B、Low values for K (like k=1 or k=2) can be noisy and subject to the effect of outliers.
C、A large k value can reduce the overall noise so the value for 'k' can be as big as possible.
D、Historically, the optimal K for most datasets has been between 3-10.
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