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Use significant attributes only, or use full set of attributes to build J48 model after checking information gain?

score 144 · Answer 1 · 2024-12-30 00:28:30

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Use significant attributes only, or use full set of attributes to build J48 model after checking information gain?

144 views Asked by Guanhua Lee At 30 December 2024 at 00:28

score 1305 · Answer 2 · 2024-12-28 22:38:35

Information Gain in R

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score 207 · Answer 3 · 2025-01-06 14:23:55

ML Decision Tree classifier is only splitting on the same tree / asking about the same attribute

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How does pessimistic error pruning in C4.5 algorithm working?

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score 1145 · Answer 5 · 2025-01-06 14:20:25

Paralleizing implementation of Decision tree ID3/C4.5 on Hadoop

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I am looking for specific algorithms in Orange

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score 1124 · Answer 7 · 2025-01-06 14:22:24

R caret train() underperforming on J48 compared to manual parameter setting

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score 113 · Answer 8 · 2025-01-06 14:16:31

Identify application based on its packets

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score 1546 · Answer 9 · 2024-12-30 00:14:24

C4.5 Decision Tree Algorithm doesn't improve the accuracy

1.5k views Asked by Dan At 30 December 2024 at 00:14

score 3934 · Answer 10 · 2025-01-07 04:26:17

c4.5 algorithm missing values

3.9k views Asked by Shubhi Shrivastava At 07 January 2025 at 04:26

TechQA.

List Question

Use significant attributes only, or use full set of attributes to build J48 model after checking information gain?

Information Gain in R

ML Decision Tree classifier is only splitting on the same tree / asking about the same attribute

How does pessimistic error pruning in C4.5 algorithm working?

Paralleizing implementation of Decision tree ID3/C4.5 on Hadoop

I am looking for specific algorithms in Orange

R caret train() underperforming on J48 compared to manual parameter setting

Identify application based on its packets

C4.5 Decision Tree Algorithm doesn't improve the accuracy

c4.5 algorithm missing values

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