machine learning - Are decision trees almost always binary trees ...
2011年6月22日 · Regarding uses of decision tree and splitting (binary versus otherwise), I only know of CHAID that has non-binary splits but there are likely others. For me, the main use of a non binary split is in data mining exercises where I am looking at how to optimally bin a nominal variable with many levels.
How would you use decision trees to learn to predict a multiclass ...
2018年11月9日 · $\begingroup$ You can use any form of tree as a decision tree. There's no restriction to two children per node. There's no restriction to two children per node. In a binary tree each decision is a Yes/No decision but you can of course also model A/B/C decisions where you have more than two alternatives. $\endgroup$
Decision tree for searching element in sorted-array
2022年5月1日 · But my teacher-assistant told me that when we want to show a lower-bound on process, we can show it by drawing a decision-tree for any algorithm that solves the process and not just a specific one. Meaning that we want to bound the decision tree's height for any algorithm that solves the specific problem.
Decision Trees: if always binary split - Cross Validated
2016年11月8日 · CHAID Trees can have multiple nodes (more than 2), so decision trees are not always binary. There are many different tree building algorithms and the Random Forest algorithm actually creates an ensemble of decision trees. In the original paper, the authors used a slight variation of the CART algorithm. However its not necessary to use CART to ...
What is the VC dimension of a decision tree? - Cross Validated
2016年8月22日 · In a recent paper, Decision trees as partitioning machines to characterize their generalization properties by Jean-Samuel Leboeuf, Frédéric LeBlanc and Mario Marchand, the authors consider the VC dimension of decision trees on examples of $\ell$ features (which is a generalization of your question which concerns only 2 dimensions).
VC dimension of decision tree [duplicate] - Cross Validated
2018年4月25日 · The first tree can assigns the elements of a set to its 8 leaves, so it can shatter a set of 8. With a larger set, it can subdivide it into 8 sets, some with a score of +1 and some with a score of -1. Suppose without loss of generality that the first tree gave a …
Best practices for coding categorical features for Decision Trees?
2015年10月21日 · $\begingroup$ Having more than 32-level binary-encoded categories will have slightly different behavior in the tree, since RF will just select from among those binary columns, rather than selecting the single column of the factor with many levels.
classification - Size of decision tree and depth of decision tree ...
If some nodes have more than 2 children (e.g., they make a ternary decision instead of a binary decision), then the size can be even larger. So, a size of 7650 is not unreasonable, if some nodes make binary decisions and some make ternary or multi-way decisions.
VC dimension of a greedy decision tree vs a optimal decision tree
2020年11月22日 · Take the 𝐶𝐴𝑅𝑇 binary splitting tree, for example, the practical implementation is a greedy splitting procedure. With some fixed depth ℎ, one can fit an optimal decision tree (by trying every possible split). The two different training procedures would hopefully result in different trees.
Multi-class classification with binary decision tree
2019年10月24日 · I've built a decision tree for multi-class classification (MNIST). My question is, whenever I want to predict the label of a test pattern and I follow the tree depending on the values of the test pattern's attributes, what happens if there is not a left or right branch for a given test pattern attribute value?